SAHA Counteracts Host Response Alterations Driven by Carbapenem-Resistant Acinetobacter baumannii: A Transcriptomic Deep Dive

SAHA Counteracts Host Response Alterations Driven by Carbapenem-Resistant Acinetobacter baumannii: A Transcriptomic Deep Dive | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article SAHA Counteracts Host Response Alterations Driven by Carbapenem-Resistant Acinetobacter baumannii: A Transcriptomic Deep Dive Siva Singothu, Harshala Maruti Baddi, Divyasree Vulli, Hoshiyar Singh, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7084777/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Bacterial pathogens remodel the host epigenetic programming to surpass host defence mechanisms for their benefit. The studies on carbepenem-resistant A. baumannii (CRAB) circumvention of host defence mechanisms, especially the role of host HDAC inhibition on its survival, have not been investigated. In the current study, we employed comparative transcriptomics to investigate changes in the key host pathways and biological processes during A. baumannii infection and after its treatment with SAHA (pan HDAC inhibitor). Our primary findings highlighted that A. baumannii establishes an immunosuppressive condition by regulating both TNFα and IL10 signaling pathways for its persistence. We found overexpression of the ACOD1 gene during infection, which is reportedly involved in the progression of sepsis. In the presence of SAHA, the mRNA expression of IDO1, ACOD1, IL10RA, IL10, TNFα, IL6, IFNB1, and CCL3L3 genes was found to be decreased during AB infection. Further, we observed that SAHA treatment induces autophagy by regulating the genes involved in phagosome maturation and antigen processing through tubulin binding and MHC class II proteins, respectively. Moreover, SAHA facilitates the autophagosome-lysosome fusion process through upregulation of important autophagy-related and SNARE proteins, causing bacterial clearance. Therefore, our findings provide a comprehensive insight into the A. baumannii immune evasion mechanisms and the potential of SAHA as a host-directed therapeutic against A. baumannii infection. Transcriptomics Acinetobacter baumannii Histone protein modifications Autophagy and Host-directed therapy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Host-directed therapy (HDT) is a burgeoning approach for treating infectious diseases, it primarily focuses on host signaling pathways rather than acting upon the pathogens. The aim is to boost the host's defense mechanisms and mitigate pathogen-induced cell death while reducing the risk of anti-microbial resistance (AMR) [ 1 ]. In the current scenario, AMR has become a global health threat, causing 1.2 million deaths yearly. With the lack of new antimicrobials, the death rate may rise to 10M per year by 2050 [ 2 ]. Therefore, HDT serves as an alternative therapeutic option to tackle multidrug-resistant (MDR) pathogens by activating host defense mechanisms. Earlier reports showed that various pathogens learned to evade host defense mechanisms by altering the epigenetic machinery for their survival inside the host [ 3 – 6 ]. During pathogen invasion, upregulation of histone deacetylase (HDACs) enzymes leads to host histone protein modification, which supports pathogen survival by decreasing the expression of host defense genes and inducing immunosuppression is mainly reported [ 7 – 10 ]. In our previous study, we explored the regulation of histone acetylation in the THP-1 cell line infected with Carbapenem-resistant A. baumannii (CRAB) [ 11 ]. CRAB is an opportunistic gram-negative bacteria responsible for nosocomial infectious diseases and also listed as a critical group pathogen in the global bacterial priority pathogen list (PPL) by the World Health Organization (WHO) [ 12 – 14 ]. After infection with CRAB, we observed decreased acetylation levels of the histone proteins, H3K9ac, H3K27ac, and H2AK5ac and upregulation of five HDACs (HDAC1, HDAC4, HDAC6, HDAC7, and HDAC11) in THP-1 cells. Further, we used a pan-HDAC inhibitor-vorinostat (SAHA), to inhibit HDACs, which resulted in the restoration of histone acetylation levels and decreased survival of intracellular CRAB, previously [ 11 ]. Further to delve into the mechanism by which SAHA treatment leads to reduced CRAB burden and to identify the host transcripts involved in this modulation, we employed a comparative transcriptomic approach to investigate the host transcriptional changes. The present study will provide, for the first time, comprehensive insights into the host changes due to CRAB infection and highlight the potential of SAHA or HDAC inhibition in decreasing CRAB burden. This investigation will also shed light on the key host pathways, processes and genes involved in CRAB infection, identifying potential targets for HDT. Results The host exhibits a plethora of gene modulation events in response to A. baumannii infection and SAHA treatment In the current study, we performed comparative RNA sequencing analysis among: i) AB-infected and uninfected control cells (AB vs C), ii) AB-infected cells with and without SAHA treatment (SAB vs AB) and iii) SAHA-treated cells with and without AB infection (SAB vs SC). Our transcriptomics analysis data revealed significant modulation of gene expression caused by AB, as well as in SAHA-treated AB-infected cells in comparison to their respective controls. We performed PCA to know the dynamic changes of gene expression in all groups and observed a positive correlation between the biological replicates of each group (Fig. 1 a). Besides, we also used a hierarchical clustering heatmap to validate the correlation of gene expression in all pairwise combinations in groups (Fig. 1 b). The PCA plot and hierarchical clustering heatmap showed a clear difference in gene expression in AB-infected and SAHA-treated groups. Further, we determined the complete DEGs profile of each group, in AB vs C, we found 1359 DEGs (845 upregulated and 514 downregulated), in SAB vs AB, 3850 DEGs (2032 upregulated and 1818 downregulated) and in SAB vs SC, 167 DEGs (162 upregulated and 5 downregulated) were observed (Fig. 1 c). We also observed the common DEGs between the groups by plotting a Venn diagram (Fig. 1 d). Interestingly, we found a reduced number of DEGs in the SAHA-treated group compared to the SAHA control, that implicit A. baumannii could not regulate mRNA expression to survive in the SAHA pre-treated group. Moreover, we plotted a heatmap of all DEGs between the groups to observe the expression pattern of genes (Fig. 1 e). A. baumannii creates immunosuppressive conditions for its survival in the host Functional analysis of DEGs between AB and C was carried out to understand the modulations done by CRAB. Gene ontology (GO) revealed that most DEGs fell in the host's defensive mechanism against infection. We observed a few signaling biological processes showing high enrichment scores among all which included i) response to the virus, ii) response to lipopolysaccharide (LPS), iii) response to molecule of bacterial origin, and iv) defense response to the virus, which might contribute to tackling A. baumannii in the early inflammatory phase (Fig. 2 a). Further, we generated an emap plot to know the relations between the enriched biological processes. The biological process (“response to LPS”) has shown strong relationships with all processes that regulate the release of cytokines during AB infection ( Figure S1 ). Later, we performed protein-protein interaction (PPI) network analysis by STRING database for the DEGs present in response to LPS biological process. It revealed that the genes were majorly involved in the TNF signaling pathway (KEGG ID: hsa04668, DEGs were highlighted in blue color) and IL10 signaling pathway (Reactome pathway ID: HSA-6783783, DEGs was highlighted in red color) (Fig. 2 b), which have a connection with inflammatory-related genes and also responsible for immunosuppression in late infection stage [ 15 – 17 ]. The volcano plot analysis also showed that the genes IL10RA, IL6, TNF alpha, and IL1β were upregulated during AB infection (Fig. 2 c). Further, KEGG pathway analysis also showed the DEGs majorly involved in the inflammation-associated pathways, such as i) cytokine-cytokine receptor interaction (KEGG ID: hsa04060), ii) TNF signaling pathway (KEGG ID: hsa04668), and iii) NF-kappa B signaling pathway (KEGG ID: hsa04064), may have contributed to causing inflammation, which further progresses to sepsis (Fig. 2 d). Interestingly, we observed that cis-aconitate decarboxylase 1 (ACOD1) gene was upregulated in the A. baumannii-infected group and have connection with pro-inflammatory cytokines such as IL6, TNF, and IL1β (Fig. 2 e). SAHA allayed the transcriptional changes caused by A. baumannii Later, we analyzed the DEGs in SAB and observed decreased expression of pro-inflammatory cytokines (IL6 and TNFα), ACOD1 and IL10RA during infection (Fig. 3 a). Moreover, we also observed the upregulation of S100 family proteins such as S100A9 and S100A12 in the presence of SAHA, which are antimicrobial peptides that restrict the availability of metal ions to starve the bacteria [ 18 , 19 ]. We also found that DEGs' highly enriched molecular function was tubulin binding (GO: 0015631) and microtubule binding (GO: 0008017) in the presence of SAHA (Fig. 3 b). Next, we performed a KEGG pathway analysis that revealed phagosome (KEGG pathway ID: hsa04145) formation is the most enriched pathway in the presence of SAHA (Fig. 3 c), which is substantially related to other enriched pathways such as tuberculosis, leishmaniasis, and rheumatoid arthritis ( Figure S2 ). Besides, we plotted a heatmap of DEGs present in the phagosome KEGG pathway (Fig. 3 d), and observed distinguished gene expression in SAHA-treated groups [SAHA control (SC) and infected + SAHA (SAB)] compared to infected (AB1 and AB2) and uninfected (C1 and C2), and network analysis of phagosome pathway also showed that the upregulation of tubulin binding proteins (TUBB3, TUBB2B, and TUBB4A) and major histocompatibility (MHC) class II proteins (HLA-DMA, HLA-DPA1, HLA-DMB, HLA-DQA1, and HLA-DQB1) (Fig. 3 e), which regulates the formation of phagosome during bacterial infection and also antigen presentation and processing in MHC class II molecules that crucial for recruiting helper CD4 + T cells to execute adaptive immunity [ 20 – 23 ]. Therefore, SAHA treatment leading to HDAC inhibition may have induced autophagy to kill A. baumannii by upregulating S100A9 (Fig. 3 f) and also decreasing the expression of ACOD1 (Fig. 3 g). SAHA promotes S100A9-mediated autophagy to retard the survival of A. baumannii intracellularly The phagocytic effect of SAHA mainly depends on the upregulation of S100 family proteins such as S100A5 ( Figure S3a ), calgranulin B (S100A9) ( Figure S3b ), and calgranulin C (S100A12) ( Figure S3c ), which limit the availability of essential metal ions (zinc, iron, and manganese) at infection foci to starve bacteria in a process called “nutritional immunity” [ 19 ]. Previous studies enlightened the role of antimicrobial peptides (S100A9 and S100A12) in the progression of autophagy to degrade intracellular bacteria and also in the restriction of bacterial invasion by inhibiting binding to the epithelial cells [ 24 – 26 ]. Therefore, we analyzed the effect of antimicrobial peptides on the autophagy process in the presence of SAHA during A. baumannii infection. Initially, we looked into the expression of genes involved in the autophagosome formation, such as ATG9B (initiation- phagophore formation), ATG12 system (ATG16L1 and ATG5) and ATG8 system (ATG4C, LC3, and GABARAP) that are involved in the initiation, elongation and maturation of autophagosomes (Fig. 4 a). SAHA treatment successfully activated autophagy by significantly upregulating ATG9B (p < 0.001), and ATG16L1 (p < 0.001), ATG5 (p < 0.05), ATG4C (p < 0.001), GABARAP (p < 0.01) compared to the infected group (Fig. 4 b- 4 f). In addition, the conversion of LC3-I to LC3-II also increased in SAHA-treated groups (Fig. 4 g & S4a). Further, we determined the expression of genes involved in the autophagosome and lysosome fusion process (Fig. 4 h). Majorly, SNARE proteins (VAMP7, STX7, STX17, YKT6, and SNAP proteins such as SNAP25/29/47) present on the autophagosome and lysosome participate in the fusion process. We also observed significant increase of VAMP7, STX7, STX17, YKT6, and SNAP25/29/47 mRNA expression (Fig. 4 i- 4 o), which promotes fusion process to eliminate A. baumannii , also confirmed by the decreased of P62 level after autophagy completion (Fig. 4 p & S4b). In addition, we used lentivirus transduction to introduce the mCherry-GFP-LC3B construct into THP-1 cells in order to monitor the fusion of autophagosomes with lysosomes ( Fig. 5 a ) . The free autophagosomes contain both GFP-LC3B (green) and mCherry-LC3B (red), resulting in a yellow fluorescence (mCherry + GFP + ). In contrast, autolysosomes display only red fluorescence (mCherry + GFP − ), due to the degradation of GFP in the acidic lysosomal environment [ 27 ]. To assess the fusion process, the ratio of mCherry-LC3B to GFP-LC3B fluorescence intensity was used. In this study, we observed that the ratio was reduced in the infected group and in cells treated with standard autophagy inhibitors (chloroquine and bafilomycin A1), suggesting an accumulation of autophagosomes (yellow: mCherry + GFP + ) due to impaired fusion with lysosomes, in contrast to the increased ratio was observed in uninfected, SAHA and rapamycin (standard autophagy activator) treated groups ( Fig. 5 b and 5 c ) . Furthermore, we also observed that expression of LAMP3 was increased in A. baumannii infected groups (Fig. 6 a). A recent study reported that high expression of LAMP3 inhibits autophagy through LAMP1 degradation by releasing cathepsin B and cathepsin D that activate caspase 1 and caspase 3 pathways [ 28 ]. These findings suggest that A. baumannii may evade host defenses by disrupting the autophagic process. RNA Seq data validation We validated our RNA seq data using qPCR. The upregulated genes (IL6, TNFα, IFNB1, CCL3L3, IDO1, ACOD1, IL10, IL10RA) and downregulated genes (GPR65, HEY2, and SASH3) during A. baumannii infection was selected. All the genes followed the same trend as observed in RNA seq. As discussed in RNA-Seq data analysis, we observed a significant increase of ACOD1 in the A. baumannii infected group, which is reportedly involved in the progression of sepsis. In the presence of SAHA, we found that the mRNA expression of IDO1, ACOD1, IL10RA, IL10, TNFα, IL6, IFNB1, and CCL3L3 genes was decreased during A. baumannii infection (Fig. 6 b- 6 i). Further, validation of downregulated genes was performed, and decreased expression of GPR65, HEY2, and SASH3 was observed in A. baumannii infected compared to uninfected ( Figure S5a-c ). Here, we didn’t observe any changes in downregulated genes in the SAHA-treated group except the SASH3 gene, which showed a significant increase in the SAHA-treated group compared to the A. baumannii-infected group. Discussion In the present study for the first time, we have attempted to showcase the pathways and genes modulated by A. baumannii for its survival in the host. Especially, histone modifications which are the key regulators in innate immune defense response against bacterial invasion [ 29 , 30 ]. However, bacteria employ various strategies to survive intracellularly by altering the status of histone acetylation level (H3K9ac and H3K27ac) and histone methylation level (H3K27me3) in the host that affects the transcription of immune defense genes [ 31 , 32 ]. Hence, we analyzed the transcriptomic data to find DEGs that regulates the survival of A. baumannii in the presence of SAHA. SAHA treatment will increase histone acetylation levels by inhibiting HDACs and promoting transcription of immune defense genes [ 33 ]. After infection, we didn’t observe any changes in the DEGs number in the infected + SAHA (SAB) group compared to SAHA control (SC) that denotes A. baumannii was not able to alter the gene expression in presence of SAHA. Despite that, infected (AB) group showed a high number of DEGs in comparison to uninfected (C) group. Majorly, we seen inflammatory pathways such as cytokine-cytokine receptor interaction, TNF signaling pathway and NF-κB signaling pathways were enriched during infection, along with anti-inflammatory genes (e.g. IL10, IL10RA) that might contribute to sepsis. In addition, we also found that ACOD1 was upregulated in AB group compared to uninfected, which is reported to have a role in the sepsis progression. Previously, ACOD1 known as immune-responsive gene 1 (IRG1) which increases the production of itaconate, which exhibits antimicrobial and anti-inflammatory responses [ 34 – 36 ]. However, recent studies suggested that ACOD1 causes sepsis by exaggerating pro-inflammatory cytokines release through TLR4/NF-κB signaling pathway in Staphylococcus aureus induces sepsis, CDK2/Jnu signaling and AGE-AGER pathway during cecal ligation and puncture (CLP) induced polymicrobial sepsis in mice [ 37 – 39 ]. ACOD1 deficiency increases the survival of mice and decreases pro-inflammatory response [ 39 , 40 ]. Therefore, ACOD1 could be a promising HDT target for treating A. baumannii -induced septic conditions. In the presence of SAHA, the DEGs include IL6, TNF, IL10RA, and ACOD1 were downregulated, which denotes SAHA might restrict A. baumannii persistence. In support of that, we observed that anti-microbial peptides (S100A9, S100A5, and S100A12) were upregulated and DEGs involved in the tubulin-binding and microtubules binding processes were highly enriched in SAHA treated group. In addition, KEGG pathway analysis revealed that the phagosome pathway is the highly enriched pathway in the presence of SAHA. The genes present in the phagosome pathway include i) tubulin binding proteins (TUBB3, TUBB2B, and TUBB4A), and ii) MHC class II proteins (HLA-DMA, HLA-DPA1, HLA-DMB, HLA-DQA1, and HLA-DQB1) were upregulated and also involved in the phagosome formation, antigen presenting and processing in MHC class II proteins containing vesicles. Several studies emphasized the role of anti-microbial peptides (S100A9 and S100A12), tubulin binding proteins in regulating autophagy and MHC class II molecules in antigen presentation and processing during bacterial infections [ 20 , 41 – 43 ]. HDAC inhibition increases S100A9 and S100A12 level that induces autophagy process to increase clearance of Salmonella enterica serovar Typhimurium intracellularly [ 24 , 44 ]. Therefore, we further examined the genes involved in the various phases of autophagy progression. First, we observed that ATG9B was significantly increased in SAHA treated group after A. baumannii infection. Importantly, ATG9B is involved in the phagophore formation from the membrane, which is a crucial step for autophagosome formation. The deficiency of ATG9B suppresses the autophagy process [ 45 ]. Further, we have looked into the expression of ATG16L1, ATG5, ATG4C, LC3, and GABARAP genes which plays an important role in elongation and maturation of autophagosome [ 46 , 47 ]. Interestingly, ATG16L1 and ATG4C gene expression was decreased in infected group, while ATG16L1, ATG5, ATG4C and GABARAP was significantly upregulated in SAHA treated group after infection. Besides, we observed that SAHA treatment increases conversion of LC3-I to LC3-II, which is mediated by ATG4C expression. Therefore, we concluded that SAHA induces autophagy by activating genes involved in i) initiation (ATG9B - phagophore formation), and ii) elongation and maturation (ATG16L1, ATG5, ATG4C, LC3, and GABARAP) of autophagosome formation. Previously, studies reported that SAHA induces autophagy by inhibiting HDACs [ 48 – 51 ]. Next, we investigated the effect of SAHA treatment on autophagosome and lysosome fusion process to hinder the A. baumannii survival. The SNARE proteins (VAMP7, STX7, STX17, and YKT6) and SNAP proteins (SNAP25/29/47) plays a vital role in the fusion process [ 52 ]. In this study, we observed increased level of VAMP7, STX7, STX17, YKT6 and SNAP25/29/47 in SAHA treated groups contributed to successful autophagosome-lysosome process. Importantly, STX7 and SNAP 29/47 expression was decreased in A. baumannii infected group. Previous studies suggested that fusion is mediated by SNARE complexes, which forms a bridge between autophagosome and lysosome [ 53 , 54 ]. Mainly, two complexes such as STX17-SNAP29/47-VAMP7 and STX7-SNAP29/47-YKT6 were observed to mediate the fusion in the presence of SAHA to clear A. baumannii intracellularly. Besides, P62 level was decreased in SAHA treated group, which indicates the completion of autophagosome and lysosome fusion. Our results suggested that A. baumannii surviving inside the cells by inhibiting autophagosome-lysosome fusion indicated by increased p62 level. Lack of VAMP7 or ATG9B inhibits fusion process and accumulates p62 protein level [ 55 , 56 ]. In addition, mCherry-LC3B /GFP-LC3B ratio was significantly decreased in AB infected group and in the presence of autophagy inhibitors (chloroquine and Bafilomycin A1) that clearly indicates the accumulation of autophagosomes (mCherry-GFP-LC3B: yellow color) and reduced fusion between the autophagosome and lysosome. In case of SAHA treatment and rapamycin, mCherry-LC3B /GFP-LC3B ratio was significantly increased which denotes completion of fusion and formation of autolysosome (mCherry-LC3B: red color) compared with AB infection. Several studies reported that the outer membrane proteins (OmpA, and Omp33-36) of A. baumannii responsible for its persistence inside the host, which regulates CaMKK2-AMPK-ULK1 pathway, mTOR signaling pathway, and MAPK/JNK signaling pathways to inhibits autophagy process [ 57 – 60 ]. In conclusion, our results provide the understanding of mechanisms evaded by A. baumannii through host histone modifications. Mainly, A. baumannii hinders the autophagosome-lysosome fusion process to survive intracellularly. However, SAHA treatment activates autophagy and facilitates the fusion processes through important autophagy-related and SNARE proteins. Therefore, these findings demonstrate that HDAC inhibition by SAHA shows potential in decreasing bacterial survival by activating autophagy and immune pathways modulated during A. baumannii infection. Material and methods Bacterial culture condition In this study, we used a CRAB clinical isolate (AB) obtained from ESIC hospital (Hyderabad, India), and the culture was maintained on a Mueller-Hinton agar (MHA) plate at 37 o C. Intracellular macrophage infection THP-1 cells were cultured in RPMI 1640 containing 10% v/v heat-inactivated fetal bovine serum (FBS), 100 IU/mL penicillin, 0.1mg/mL streptomycin, and 2mM L-glutamine at 37 o C in 5% CO 2 . Cell differentiation was performed by adding phorbol-12-myristate-13-acetate (20ng/mL, PMA) for 24 hrs. The differentiated THP-1 cells (dTHP) were washed with fresh RPMI media and pretreated with SAHA (1µM) for 24 hrs. After SAHA treatment, cells were introduced to antibiotic-free RPMI media before infection with A. baumannii for 2 hrs at a multiplicity of infection (MOI) 10, followed by three PBS washes to remove extracellular bacteria. The cells were then incubated for 4 hrs before performing RNA isolation. RNA isolation Total RNA was extracted using the TRIzol method, followed by DNase treatment to remove genomic DNA. The quality and quantity of the purified RNA were monitored using a nanodrop and bioanalyzer (RNA integrity number is > 9). RNA sequencing and data analysis Library preparation for RNA sequencing was done with Illumina-compatible NEBNext® Ultra™ II Directional RNA Library Prep Kit (New England BioLabs, MA, USA) at Genotypic Technology Pvt. Ltd., Bangalore, India. 10ng-1ug of total RNA was used for mRNA isolation, fragmentation, and priming. Fragmented and primed mRNA was further subjected to first-strand synthesis followed by second-strand synthesis. The double-stranded cDNA was purified using NEBNext sample purification beads. Purified cDNA was end-repaired, adenylated, and ligated to Illumina adapters as per NEBNext® Ultra™ II Directional RNA Library Prep protocol followed by second strand excision using USER ™ (Uracil-Specific Excision Reagent) enzyme at 37 ˚C for 15mins. Illumina universal adapters used in the study were: 5’AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCC GATCT-3’ and Index Adapter: 5’GATCGGAAGAGCACACGTCTGAACTCCAGTCAC ATCTCGTATGCCGTCTTCTGCTTG-3’. Adapter-ligated cDNA was purified using NEBNext beads and was subjected to 11 cycles for Indexing-(98˚C for 30 secs, cycling (98˚C for 10sec, 65˚C for 75sec) and 65˚C for 5min) and enriched the adapter-ligated fragments. Final PCR products (sequencing library) were purified with NEBNext beads, followed by a library quality control check. Illumina-compatible sequencing libraries were quantified by qubit fluorometer (Thermo Fisher Scientific, MA, USA), and fragment size distribution was analyzed on Agilent 2200 TapeStation. Raw reads were processed by trimming adaptors and removing low-quality bases, dropping too short reads using trimmomatic-0.39. Later, the FASTQC tool was used to obtain the quality-filtered reads. The filtered reads were aligned to the reference genome human GRCh38 by HISAT2 and quantified by the feature counts tool [ 61 , 62 ]. After quantification, the counts were used to obtain differentially expressed genes (DEGs) using DESeq2 in R studio [ 63 ]. We performed sample-level quality control using principle component analysis (PCA) and hierarchical clustering to explore the similarity between the samples. Further, DEGs were plotted in Venn diagram using Venny 2.1 ( https://bioinfogp.cnb.csic.es/tools/venny/index.html ), a volcano plot, a violin plot and gene enrichment analysis were generated by SRplot, and a heatmap was generated by pheatmap in R studio [ 64 ]. Quantitative polymerase chain reaction (qPCR) The validation of DEGs was performed using qPCR. Total RNA was extracted by using Nucleospin RNA kit (M-N) according to the manufacturer's instructions. Further, cDNA synthesis was done using Prime script 1st strand synthesis kit (Takara). 20ng of cDNA was used to perform qPCR using TB Green Premix Ex Taq II (Takara) in the QuantStudio 7 Pro instrument. GAPDH was used as the internal control. A list of primers used were given in Table S1 . Western blotting After infection, cells were lysed by RIPA buffer containing protease inhibitor cocktail (cat no: ML051, Himedia) and centrifuged for 10mins at 10,000 rpm to collect supernatant. Later, the protein concentration in each group was quantified by bicinchoninic acid (BCA) assay kit (cat no: BCA1-1KT, Sigma Aldrich) and performed western blotting as described previously [ 65 ]. Briefly, Laemmli buffer was used to prepare the protein sample at 95 o C for 10 mins in the presence of β-mercaptoethanol. Later, 40 µg of protein was run on SDS-PAGE gel followed by protein transfer on the PVDF membrane. The membrane was kept in blocking buffer (3% BSA) for 2 hrs after transfer and incubated with primary antibodies include LC3-I/II (cat no:12741S, CST) and P62 (cat no:18420-1-AP, ThermoFisher) overnight at 4 o C. Later, the membrane was incubated with a secondary antibody (1:3000) at room temperature for 2 hrs after three washes with TBST buffer. Finally, the protein on the membrane was visualized in a chemidoc imaging system (Biorad) using enhanced chemiluminescence solution. Transfection, lentivirus preparation and stable GFP-mCherry-LC3B cell preparation HEK293T cells were seeded in a 100mm petridish to reach 60–70% confluency for the lentivirus preparation. Before transfection, cells were serum-starved for 1hr using Opti-MEM media. Lentiviral packaging psPAX2 (Addgene# 12260), enveloping plasmid PMD2.G (Addgene# 12259), GFP-mCherry-LC3B plasmid (Addgene # 170446) were mixed at a 4:2:1 ratio in Opti-MEM [ 66 ]. Transfection was performed using the lipofectamine 3000 transfection kit (Thermofisher # L3000001). Briefly, DNA-P3000 and lipofectamine 3000 were mixed and co-transfected in HEK293T cells overnight for efficient transfection. Next day, cell media changed to DMEM high glucose with 20% FBS and incubated for an additional 48hr and 72hr virus secretion and harvesting. Cell supernatant containing virus particles was collected and passed through 0.45µM PES syringe filter to remove cellular parts and stored in -80 °c for further use. Later, THP-1 cell were seeded at 1x10 5 cells/well in 6 6-well plate and transduced with 500µl lentivirus soup and polybrene at 8µg/ml for 24hr. Cells were checked every day for GFP and mCherry expression as a stable insertion of the GFP-mCherry-LC3B plasmid into cells. Immunofluorescence After transfection, we differentiated THP-1 cells with PMA 20 ng/ml for 24 hrs followed by SAHA treatment for 24 hrs. Further, we infected SAHA treated cells with A. baumannii for 2 hrs and washed with PBS, 3 times and incubated for 4 hrs. Autophagy activator (rapamycin, 500 nM, 24hrs) and autophagy inhibitors (chloroquine (20 µM, 24hrs) and bafilomycin A1 (20 nM, 24hrs) were used as standards to evaluate the autophagy flux in terms of mCherry-LC3B/ GFP-LC3B ratio. After infection, cells were fixed with 4% paraformaldehyde for 10mins and membrane permeabilization was done by 1% Triton-X 100 for 10 mins at RT. Further, cells were mounted with fluoromount-G with DAPI (cat no: 00-4959-52, Invitrogen) and images were taken by confocal microscope (Leica TCS SP8) at scale bar of 5 µm. Statistical analysis We used GraphPad Prism V8 software to analyse statistical significance between the samples by applying one-way ANOVA with tukey’s multiple comparison test. Declarations Ethics approval and consent to participate: Not Applicable Acknowledgements We acknowledge the support of National Institute of Pharmaceutical Education and Research, Hyderabad, and Department of Pharmaceuticals (DoP), Ministry of Chemical and Fertilizer for conducting this work. Funding The part of the work was supported by the Indian Council of Medical Research (ICMR) IIRP-4907. S.S. thanks DoP for providing funding for this work. Data availability RNA Seq data used in this study are available with BioProject Accession number PRJNA1276157. Consent for publication: All authors have given consent for publication. Competing interest: None to declare Authors' contributions: SS: Conceptualised the idea, study design, performed the experiments, analysed the data, drafted and edited the manuscript. HMB and DV: Performed experiments, data analysis, and manuscript editing. HS and SKG: Performed transfection experiments. RKB: study supervision and manuscript editing . VB: Study design conceptualised the idea, supervision, resource arrangements, manuscript editing and finalisation of the draft. Authors' information 1 Department of Biological Sciences, National Institute of Pharmaceutical Education and Research (NIPER), Hyderabad, Telangana – 500037, India Siva Singothu 1 , Harshala Maruti Baddi 1 , Divyasree Vulli 1 , Hoshiyar Singh 1 , Santosh Kumar Guru 1 , Vasundhra Bhandari 1 2 Department of General Medicine, ESIC Hospital, Sanath Nagar, Hyderabad, Telangana – 500038, India Rajiv Kumar Bandaru References Shapira T, Christofferson M, Av-Gay Y. The antimicrobial activity of innate host-directed therapies: A systematic review. Int J Antimicrob Agents [Internet]. 2024;63:107138. Available from: https://www.sciencedirect.com/science/article/pii/S0924857924000566 Naghavi M, Vollset SE, Ikuta KS, Swetschinski LR, Gray AP, Wool EE, et al. Global burden of bacterial antimicrobial resistance 1990–2021: a systematic analysis with forecasts to 2050. Lancet [Internet]. 2024;404:1199–226. Available from: https://doi.org/10.1016/S0140-6736(24)01867-1 Fol M, Włodarczyk M, Druszczyńska M. Host Epigenetics in Intracellular Pathogen Infections. Int. J. Mol. Sci. 2020. Thomas SS, Abhinand K, Menon AM, Nair BG, Kumar GB, Arun KB, et al. Epigenetic Mechanisms Induced by Mycobacterium tuberculosis to Promote Its Survival in the Host. Int. J. Mol. Sci. 2024. Rajeev R, Dwivedi AP, Sinha A, Agarwaal V, Dev RR, Kar A, et al. Epigenetic interaction of microbes with their mammalian hosts. J Biosci [Internet]. 2021;46:94. Available from: http://europepmc.org/abstract/MED/34728591 KavianFar A, Taherkhani H, Ahmadi A, Salimi M, Lanjanian H, Masoudi-Nejad A. Restoring the epigenetic landscape of lung microbiome: potential therapeutic approach for chronic respiratory diseases. BMC Pulm Med [Internet]. 2024;24:2. Available from: https://doi.org/10.1186/s12890-023-02789-7 Heim CE, Bosch ME, Yamada KJ, Aldrich AL, Chaudhari SS, Klinkebiel D, et al. Lactate production by Staphylococcus aureus biofilm inhibits HDAC11 to reprogramme the host immune response during persistent infection. Nat Microbiol. 2020;5:1271–84. Bandyopadhaya A, Tsurumi A, Maura D, Jeffrey KL, Rahme LG. A quorum-sensing signal promotes host tolerance training through HDAC1-mediated epigenetic reprogramming. Nat Microbiol. 2016;1:1–9. Sengupta S, Nayak B, Meuli M, Sander P, Mishra S, Sonawane A. Mycobacterium tuberculosis phosphoribosyltransferase promotes bacterial survival in macrophages by inducing histone hypermethylation in autophagy-related genes. Front Cell Infect Microbiol. 2021;11:676456. Piatek P, Namiecinska M, Lewkowicz N, Kulińska-Michalska M, Jabłonowski Z, Matysiak M, et al. Histone H3 posttranslational modified enzymes defined neutrophil plasticity and their vulnerability to IL-10 in the course of the inflammation. J Inflamm. 2024;21:16. Singothu S, Kinkar D, Vulli D, Brahma U, Bandaru RK, Bhandari V. Dysregulation of Host Histone Acetylation by Acinetobacter baumannii: A Novel Mechanism for Autophagy Inhibition and Bacterial Survival. ACS Infect Dis [Internet]. 2025; Available from: https://doi.org/10.1021/acsinfecdis.5c00080 Ahuatzin-Flores OE, Torres E, Chávez-Bravo E. Acinetobacter baumannii, a Multidrug-Resistant Opportunistic Pathogen in New Habitats: A Systematic Review. Microorganisms. 2024. Nguyen M, Joshi SG. Carbapenem resistance in Acinetobacter baumannii, and their importance in hospital‐acquired infections: a scientific review. J Appl Microbiol [Internet]. 2021;131:2715–38. Available from: https://doi.org/10.1111/jam.15130 Sati H, Carrara E, Savoldi A, Hansen P, Garlasco J, Campagnaro E, et al. The WHO Bacterial Priority Pathogens List 2024: a prioritisation study to guide research, development, and public health strategies against antimicrobial resistance. Lancet Infect Dis [Internet]. 2025; Available from: https://doi.org/10.1016/S1473-3099(25)00118-5 Ben-Khemis M, Liu D, Pintard C, Song Z, Hurtado-Nedelec M, Marie J-C, et al. TNFα counteracts interleukin-10 anti-inflammatory pathway through the NOX2-Lyn-SHP-1 axis in human monocytes. Redox Biol [Internet]. 2023;67:102898. Available from: https://www.sciencedirect.com/science/article/pii/S2213231723002999 CHAUDHRY H, ZHOU J, ZHONG YIN, ALI MIRM, MCGUIRE F, NAGARKATTI PS, et al. Role of Cytokines as a Double-edged Sword in Sepsis. In Vivo (Brooklyn) [Internet]. 2013;27:669 LP – 684. Available from: http://iv.iiarjournals.org/content/27/6/669.abstract Friedman G, Jankowski S, Marchant A, Goldman M, Kahn RJ, Vincent JL. Blood interleukin 10 levels parallel the severity of septic shock. J Crit Care [Internet]. 1997;12:183–7. Available from: https://www.sciencedirect.com/science/article/pii/S0883944197900307 Kozlyuk N, Monteith AJ, Garcia V, Damo SM, Skaar EP, Chazin WJ. S100 Proteins in the Innate Immune Response to Pathogens BT - Calcium-Binding Proteins of the EF-Hand Superfamily: From Basics to Medical Applications. In: Heizmann CW, editor. New York, NY: Springer New York; 2019. p. 275–90. Available from: https://doi.org/10.1007/978-1-4939-9030-6_18 Zackular JP, Chazin WJ, Skaar EP. Nutritional Immunity: S100 Proteins at the Host-Pathogen Interface *. J Biol Chem [Internet]. 2015;290:18991–8. Available from: https://doi.org/10.1074/jbc.R115.645085 Ligeon L-A, Pena-Francesch M, Vanoaica LD, Núñez NG, Talwar D, Dick TP, et al. Oxidation inhibits autophagy protein deconjugation from phagosomes to sustain MHC class II restricted antigen presentation. Nat Commun [Internet]. 2021;12:1508. Available from: https://doi.org/10.1038/s41467-021-21829-6 Santa K. Macrophages: Phagocytosis, Antigen Presentation, and Activation of Immunity. In: Athari SS, Nasab EM, editors. Rijeka: IntechOpen; 2023. Available from: https://doi.org/10.5772/intechopen.110832 Duraes F V, Niven J, Dubrot J, Hugues S, Gannagé M. Macroautophagy in Endogenous Processing of Self- and Pathogen-Derived Antigens for MHC Class II Presentation. Front Immunol [Internet]. 2015;Volume 6-. Available from: https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2015.00459 Roche PA, Furuta K. The ins and outs of MHC class II-mediated antigen processing and presentation. Nat Rev Immunol [Internet]. 2015;15:203–16. Available from: https://doi.org/10.1038/nri3818 Schulthess J, Pandey S, Capitani M, Rue-Albrecht KC, Arnold I, Franchini F, et al. The short chain fatty acid butyrate imprints an antimicrobial program in macrophages. Immunity. 2019;50:432-445. e7. Kanokwan N, F. RK, C. HM. Calprotectin Expression Inhibits Bacterial Binding to Mucosal Epithelial Cells. Infect Immun [Internet]. 2001;69:3692–6. Available from: https://doi.org/10.1128/iai.69.6.3692-3696.2001 Champaiboon C, Sappington KJ, Guenther BD, Ross KF, Herzberg MC. Calprotectin S100A9 Calcium-binding Loops I and II Are Essential for Keratinocyte Resistance to Bacterial Invasion *. J Biol Chem [Internet]. 2009;284:7078–90. Available from: https://doi.org/10.1074/jbc.M806605200 Kim S, Choi S, Kang D. Quantitative and qualitative analysis of autophagy flux using imaging. BMB Rep [Internet]. 2020/05/31. 2020;53:241–7. Available from: https://www.bmbreports.org/journal/view.html?doi=10.5483/BMBRep.2020.53.5.046 Tanaka T, Blake M. W, Drew G. M, Hiroyuki N, Toshio O, Hongen Y, et al. LAMP3 inhibits autophagy and contributes to cell death by lysosomal membrane permeabilization. Autophagy [Internet]. 2022;18:1629–47. Available from: https://doi.org/10.1080/15548627.2021.1995150 Li X, Ye Y, Peng K, Zeng Z, Chen L, Zeng Y. Histones: The critical players in innate immunity. Front Immunol [Internet]. 2022;Volume 13. Available from: https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2022.1030610 Hamon MA, Cossart P. Histone Modifications and Chromatin Remodeling during Bacterial Infections. Cell Host Microbe [Internet]. 2008;4:100–9. Available from: https://www.sciencedirect.com/science/article/pii/S193131280800228X Lin Y, Qiu T, Wei G, Que Y, Wang W, Kong Y, et al. Role of Histone Post-Translational Modifications in Inflammatory Diseases. Front Immunol [Internet]. 2022;Volume 13. Available from: https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2022.852272 Wu D, Shi Y, Zhang H, Miao C. Epigenetic mechanisms of Immune remodeling in sepsis: targeting histone modification. Cell Death Dis [Internet]. 2023;14:112. Available from: https://doi.org/10.1038/s41419-023-05656-9 Xu T, Fang Y, Gu Y, Xu D, Hu T, Yu T, et al. HDAC inhibitor SAHA enhances antitumor immunity via the HDAC1/JAK1/FGL1 axis in lung adenocarcinoma. J Immunother Cancer [Internet]. 2024;12:e010077. Available from: http://jitc.bmj.com/content/12/10/e010077.abstract Li R, Zhang P, Wang Y, Tao K. Itaconate: A Metabolite Regulates Inflammation Response and Oxidative Stress. Oxid Med Cell Longev [Internet]. 2020;2020:5404780. Available from: https://doi.org/10.1155/2020/5404780 Coelho C. Itaconate or how I learned to stop avoiding the study of immunometabolism. PLOS Pathog [Internet]. 2022;18:e1010361. Available from: https://doi.org/10.1371/journal.ppat.1010361 Al Akiki Dit Al Mazraani R, Malys N, Maliene V. Itaconate and its derivatives as anti-pathogenic agents. RSC Adv [Internet]. 2025;15:4408–20. Available from: http://dx.doi.org/10.1039/D4RA08298B Dai F, Zhang X, Ma G, Li W. ACOD1 mediates Staphylococcus aureus-induced inflammatory response via the TLR4/NF-κB signaling pathway. Int Immunopharmacol [Internet]. 2024;140:112924. Available from: https://www.sciencedirect.com/science/article/pii/S1567576924014450 Bai L, Yu H, Cai Y, Wu R, Kang R, Jia Y, et al. Itaconate drives pro-inflammatory responses through proteasomal degradation of GLO1. Biochem Biophys Res Commun [Internet]. 2025;747:151292. Available from: https://www.sciencedirect.com/science/article/pii/S0006291X25000063 Wu R, Liu J, Wang N, Zeng L, Yu C, Chen F, et al. Aconitate decarboxylase 1 is a mediator of polymicrobial sepsis. Sci Transl Med [Internet]. 2025;14:eabo2028. Available from: https://doi.org/10.1126/scitranslmed.abo2028 Tomlinson KL, Riquelme SA, Baskota SU, Drikic M, Monk IR, Stinear TP, et al. Staphylococcus aureus stimulates neutrophil itaconate production that suppresses the oxidative burst. Cell Rep [Internet]. 2023;42:112064. Available from: https://www.sciencedirect.com/science/article/pii/S221112472300075X Köchl R, Hu XW, Chan EYW, Tooze SA. Microtubules Facilitate Autophagosome Formation and Fusion of Autophagosomes with Endosomes. Traffic [Internet]. 2006;7:129–45. Available from: https://doi.org/10.1111/j.1600-0854.2005.00368.x Xia P, Ji X, Yan L, Lian S, Chen Z, Luo Y. Roles of S100A8, S100A9 and S100A12 in infection, inflammation and immunity. Immunology [Internet]. 2024;171:365–76. Available from: https://doi.org/10.1111/imm.13722 Crotzer VL, Blum JS. Autophagy and Its Role in MHC-Mediated Antigen Presentation1. J Immunol [Internet]. 2009;182:3335–41. Available from: https://doi.org/10.4049/jimmunol.0803458 Ghavami S, Eshragi M, Ande SR, Chazin WJ, Klonisch T, Halayko AJ, et al. S100A8/A9 induces autophagy and apoptosis via ROS-mediated cross-talk between mitochondria and lysosomes that involves BNIP3. Cell Res [Internet]. 2010;20:314–31. Available from: https://doi.org/10.1038/cr.2009.129 Wang N, Tan H-Y, Li S, Feng Y. Atg9b deficiency suppresses autophagy and potentiates endoplasmic reticulum stress-associated hepatocyte apoptosis in hepatocarcinogenesis. Theranostics. 2017;7:2325. Noda T, Fujita N, Yoshimori T. The late stages of autophagy: how does the end begin? Cell Death Differ [Internet]. 2009;16:984–90. Available from: https://doi.org/10.1038/cdd.2009.54 Zhao YG, Codogno P, Zhang H. Machinery, regulation and pathophysiological implications of autophagosome maturation. Nat Rev Mol Cell Biol. 2021;22:733–50. Yang J, He J, Ismail M, Tweeten S, Zeng F, Gao L, et al. HDAC inhibition induces autophagy and mitochondrial biogenesis to maintain mitochondrial homeostasis during cardiac ischemia/reperfusion injury. J Mol Cell Cardiol [Internet]. 2019;130:36–48. Available from: https://doi.org/10.1016/j.yjmcc.2019.03.008 Fröhlich LF, Mrakovcic M, Smole C, Zatloukal K. Molecular mechanism leading to SAHA-induced autophagy in tumor cells: Evidence for a p53-dependent pathway. Cancer Cell Int. 2016;16:1–15. Foggetti G, Ottaggio L, Russo D, Mazzitelli C, Monti P, Degan P, et al. Autophagy induced by SAHA affects mutant P53 degradation and cancer cell survival. Biosci Rep [Internet]. 2019;39:BSR20181345. Available from: https://doi.org/10.1042/BSR20181345 Lee JY-C, Kuo C-W, Tsai S-L, Cheng SM, Chen S-H, Chan H-H, et al. Inhibition of HDAC3- and HDAC6-Promoted Survivin Expression Plays an Important Role in SAHA-Induced Autophagy and Viability Reduction in Breast Cancer Cells. Front Pharmacol [Internet]. 2016;Volume 7-. Available from: https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2016.00081 Hikita H, Sakane S, Takehara T. Mechanisms of the autophagosome-lysosome fusion step and its relation to non-alcoholic fatty liver disease. Liver Res [Internet]. 2018;2:120–4. Available from: https://www.sciencedirect.com/science/article/pii/S2542568418300254 Jian F, Wang S, Tian R, Wang Y, Li C, Li Y, et al. The STX17-SNAP47-VAMP7/VAMP8 complex is the default SNARE complex mediating autophagosome–lysosome fusion. Cell Res. 2024;34:151–68. Zheng D, Tong M, Zhang S, Pan Y, Zhao Y, Zhong Q, et al. Human YKT6 forms priming complex with STX17 and SNAP29 to facilitate autophagosome-lysosome fusion. Cell Rep [Internet]. 2024;43:113760. Available from: https://www.sciencedirect.com/science/article/pii/S2211124724000883 Choi J, Haeun J, Zhao X, and Park D. Emerging roles of ATG9/ATG9A in autophagy: implications for cell and neurobiology. Autophagy [Internet]. 2024;20:2373–87. Available from: https://doi.org/10.1080/15548627.2024.2384349 Aoyagi K, Ohara-Imaizumi M, Itakura M, Torii S, Akimoto Y, Nishiwaki C, et al. VAMP7 regulates autophagy to maintain mitochondrial homeostasis and to control insulin secretion in pancreatic β-cells. Diabetes. 2016;65:1648–59. Kyungho W, Ho KD, Ho-Sung P, Hwan OM, Chul LJ, Hee CC. Acinetobacter baumannii OmpA hinders host autophagy via the CaMKK2-reliant AMPK-pathway. MBio [Internet]. 2025;16:e03369-24. Available from: https://doi.org/10.1128/mbio.03369-24 Carlos R, María T, Esteban FM, Cruz SN, Micaela C, Elena S, et al. The Acinetobacter baumannii Omp33-36 Porin Is a Virulence Factor That Induces Apoptosis and Modulates Autophagy in Human Cells. Infect Immun [Internet]. 2014;82:4666–80. Available from: https://doi.org/10.1128/iai.02034-14 Zhao D, Li Y, Peng C, Lin J, Yu F, Zhao Y, et al. Outer membrane protein a in Acinetobacter baumannii induces autophagy through mTOR signalling pathways in the lung of SD rats. Biomed Pharmacother [Internet]. 2021;135:111034. Available from: https://www.sciencedirect.com/science/article/pii/S0753332220312269 An Z, Huang X, Zheng C, Ding W. Acinetobacter baumannii outer membrane protein A induces HeLa cell autophagy via MAPK/JNK signaling pathway. Int J Med Microbiol. 2019;309:97–107. Kim D, Paggi JM, Park C, Bennett C, Salzberg SL. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat Biotechnol [Internet]. 2019;37:907–15. Available from: https://doi.org/10.1038/s41587-019-0201-4 Liao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics [Internet]. 2014;30:923–30. Available from: https://doi.org/10.1093/bioinformatics/btt656 Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol [Internet]. 2014;15:550. Available from: https://doi.org/10.1186/s13059-014-0550-8 Tang D, Chen M, Huang X, Zhang G, Zeng L, Zhang G, et al. SRplot: A free online platform for data visualization and graphing. PLoS One [Internet]. 2023;18:e0294236. Available from: https://doi.org/10.1371/journal.pone.0294236 Babu SSN, Singla S, Jena G. Role of combination treatment of aspirin and zinc in DMH-DSS-induced colon inflammation, oxidative stress and tumour progression in male BALB/c mice. Biol Trace Elem Res. 2023;201:1327–43. Wulansari N, Darsono WHW, Woo H-J, Chang M-Y, Kim J, Bae E-J, et al. Neurodevelopmental defects and neurodegenerative phenotypes in human brain organoids carrying Parkinson’s disease-linked DNAJC6 mutations. Sci Adv [Internet]. 2025;7:eabb1540. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7084777","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":484588429,"identity":"0caac441-dfd4-4a12-972e-63f223df5e04","order_by":0,"name":"Siva Singothu","email":"","orcid":"","institution":"National Institute of Pharmaceutical Education and Research Hyderabad","correspondingAuthor":false,"prefix":"","firstName":"Siva","middleName":"","lastName":"Singothu","suffix":""},{"id":484588430,"identity":"11165851-219d-481a-9a8a-eb503e12baac","order_by":1,"name":"Harshala Maruti Baddi","email":"","orcid":"","institution":"National Institute of Pharmaceutical Education and Research Hyderabad","correspondingAuthor":false,"prefix":"","firstName":"Harshala","middleName":"Maruti","lastName":"Baddi","suffix":""},{"id":484588431,"identity":"e227ad54-eebf-4c30-b43e-ee2e58fafa04","order_by":2,"name":"Divyasree Vulli","email":"","orcid":"","institution":"National Institute of Pharmaceutical Education and Research Hyderabad","correspondingAuthor":false,"prefix":"","firstName":"Divyasree","middleName":"","lastName":"Vulli","suffix":""},{"id":484588432,"identity":"2ed7e0bc-16f6-4199-aaab-85707c2c7dca","order_by":3,"name":"Hoshiyar Singh","email":"","orcid":"","institution":"National Institute of Pharmaceutical Education and Research Hyderabad","correspondingAuthor":false,"prefix":"","firstName":"Hoshiyar","middleName":"","lastName":"Singh","suffix":""},{"id":484588433,"identity":"09c8685e-8ff2-43ca-862e-ebb0afdb68f8","order_by":4,"name":"Santosh Kumar Guru","email":"","orcid":"","institution":"National Institute of Pharmaceutical Education and Research Hyderabad","correspondingAuthor":false,"prefix":"","firstName":"Santosh","middleName":"Kumar","lastName":"Guru","suffix":""},{"id":484588434,"identity":"36139bc0-02a2-4925-8f23-41c07b8fecfc","order_by":5,"name":"Rajiv Kumar Bandaru","email":"","orcid":"","institution":"ESIC Medical College and Hospital Hyderabad","correspondingAuthor":false,"prefix":"","firstName":"Rajiv","middleName":"Kumar","lastName":"Bandaru","suffix":""},{"id":484588435,"identity":"0841503d-4671-4cd6-826d-04458a633fcb","order_by":6,"name":"VASUNDHRA BHANDARI","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIiWNgGAWjYNACtgMMDOztBx8AmTx8xGvhOZNsANLCRrwWiQQzCTCbkGKD48efSReU3cnnb0hIq/yaYyfDxsD88NENfFrO5JhJzzj3zHLGgYPHbstuSwY6jM3YOAePFsmGHDZp3rbDBgwHG9JuS25jBmrhYZPGq6X/+TOwFvnDDGbFktvqCWvhB/oarMXgGIMZ48dth4nR8sbYmufcYQPDMzzJ0ozbjvOwMRPwCxt/+sPbPGWHDeTuPz/48ee2ant+9uaHj/FpQQHMPGCSWOUgwPiDFNWjYBSMglEwYgAA3OhFv98o6hIAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-1930-1722","institution":"National Institute of Pharmaceutical Education and Research Hyderabad","correspondingAuthor":true,"prefix":"","firstName":"VASUNDHRA","middleName":"","lastName":"BHANDARI","suffix":""}],"badges":[],"createdAt":"2025-07-09 14:38:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7084777/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7084777/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87003262,"identity":"c404c6fc-e147-45f5-aab5-92cf498c2f42","added_by":"auto","created_at":"2025-07-18 07:46:07","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":415260,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTranscriptomic profile of THP-1 cells infected with CRAB and with SAHA treatment.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea)\u003c/strong\u003e Principal-component analysis (PCA) of four individual groups, uninfected (C1 \u0026amp; C2), SAHA control (SC1 \u0026amp; SC2), Infected (AB1 \u0026amp; AB2), and Infected + SAHA (SAB1 \u0026amp; SAB2). The PCA plot denotes the two-dimensional scatterplot of two principal components (PC1 and PC2) of the RNA-Seq data of all four groups represented in different colours. Each dot represents a biological replicate. \u0026nbsp;The distance between each dot is directly related to the correlation among the samples.\u003cstrong\u003e b) \u003c/strong\u003eHierarchical clustering heatmap of RNA-Seq samples indicates the correlation of gene expression for all pairwise combinations of samples. \u003cstrong\u003ec) \u003c/strong\u003eThe bar graph of total (differentially expressed genes) DEGs number, where upregulated DEGs are represented in blue and downregulated in orange. \u003cstrong\u003ed) \u003c/strong\u003eThe Venn diagram showing the relationship of total DEGs (log fold change is 1.5, adjusted P value = 0.01) between the pairwise comparisons of i) infected vs uninfected (AB vs C), ii) infected + SAHA vs Infected (SAB vs AB), and iii) infected + SAHA vs SAHA control (SAB vs SC). \u003cstrong\u003ee) \u003c/strong\u003eHeatmap representing DEGs of all four groups (log fold change is 1.5, adjusted P value = 0.01).\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7084777/v1/c6507139b1d4143662f232e8.jpeg"},{"id":87001259,"identity":"b601b32f-b75f-4950-a578-cd086e2e04bf","added_by":"auto","created_at":"2025-07-18 07:22:07","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":584612,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComplete insights into \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eA. baumannii\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e induced transcriptomic modulations in the host.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea) \u003c/strong\u003eThe top 10 enriched biological processes affected by \u003cem\u003eA. baumannii\u003c/em\u003e infection as compared to the uninfected group. Dot size and dot color represent the number of genes present in each biological process and statistical significance [-log\u003csub\u003e10\u003c/sub\u003e (p-value)]. \u003cstrong\u003eb)\u003c/strong\u003e This network represents the protein-protein interactions of differentially expressed genes (DEGs) present in the biological process (i.e. response to LPS), identified by the string database. The functional enrichment of the DEGs is indicated with different colors, such as blue is TNF signaling pathway (false discovery rate (FDR): 7.05e\u003csup\u003e-27\u003c/sup\u003e) and red is IL10 signaling pathway (FDR: 2.37e\u003csup\u003e-32\u003c/sup\u003e). Common DEGs in both pathways are represented with half blue and half red.\u003cstrong\u003e c)\u003c/strong\u003e Volcano plot represents DEGs in the \u003cem\u003eA. baumannii\u003c/em\u003e infected group. The X-axis and Y-axis show the log\u003csub\u003e2\u003c/sub\u003e fold change (LFC) and statistical significance of DEGs, respectively. The DEGs colored blue are significantly upregulated, while orange represents significantly downregulated (adjusted p-value ≤ 0.01, LFC ≥ 1.5). Non-significant genes are denoted in gray color. \u003cstrong\u003ed) \u003c/strong\u003eKEGG pathway enrichment plot of DEGs of \u003cem\u003eA. baumannii\u003c/em\u003e infected group. Dot size and dot color represent the number of genes in each pathway and their statistical significance (-log\u003csub\u003e10\u003c/sub\u003e (p-value)). \u003cstrong\u003ee) \u003c/strong\u003eThe protein-protein interaction network of DEGs shows ACOD1 has first contact with genes such as IL6, IL1β, TNF, CXCL10, and TNFAIP3 present in the biological process i.e., response to LPS.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7084777/v1/7792eadd80af855475b9ac2d.jpeg"},{"id":87004277,"identity":"89482e86-a86c-4338-88da-5faa63ae8d65","added_by":"auto","created_at":"2025-07-18 07:54:07","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":413392,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSAHA regulates the host environment required for \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eA. baumannii\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e clearance.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea) \u003c/strong\u003eVolcano plot represents DEGs between the infected + SAHA (SAB) group and the infected (AB) group. The X-axis and Y-axis show the log\u003csub\u003e2\u003c/sub\u003e fold change (LFC) and statistical significance of DEGs, respectively. The DEGs colored green are significantly upregulated, while pink represents significantly downregulated (adjusted p-value ≤ 0.01, LFC ≥ 1.5). Non-significant genes are denoted in grey. \u003cstrong\u003eb) \u003c/strong\u003eThe top 10 enriched molecular functions of DEGs (SAB vs AB). Dot size and dot color represent the number of genes present in each molecular function process and statistical significance (-log\u003csub\u003e10\u003c/sub\u003e (p-value)). \u003cstrong\u003ec) \u003c/strong\u003eKEGG pathway enrichment plot of DEGs (SAB vs AB). \u0026nbsp;Dot size and dot color represent the number of genes in each pathway and their statistical significance [-log\u003csub\u003e10\u003c/sub\u003e (p-value)]. \u003cstrong\u003ed) \u003c/strong\u003eHeatmap shows Z-score-based expression of genes present in the KEGG phagosome pathway. The Z-score was calculated using normalized gene expression value of RNAseq data.\u0026nbsp; The red color indicates the upregulation of genes (Z \u0026gt; 0), and the blue color represents the downregulation of genes (Z \u0026lt; 0). \u003cstrong\u003ee) \u003c/strong\u003eThis network represents the protein-protein interactions of DEGs present in the phagosome pathway, identified by the string database. In the presence of SAHA, the upregulated genes were indicated by green color and the downregulated genes were indicated by beige color. \u003cstrong\u003ef \u0026amp;g)\u003c/strong\u003e Violin plots showing the expression of S100A9 and ACOD1 across all groups. The Y-axis represents log normalized counts of genes. Each violin denotes each group and the thick black bar represents the interquartile range (IQR).\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7084777/v1/b2a06982c3878c60218e24c3.jpeg"},{"id":87001264,"identity":"bc4bba0d-157a-4052-8fc9-d2f2034f01d9","added_by":"auto","created_at":"2025-07-18 07:22:07","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":703432,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSAHA treatment leads to the induction of autophagy and promotes autophagosome-lysosome fusion to clear \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eA. baumannii\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea) \u003c/strong\u003eSchematic diagram of the autophagosome formation with the following steps: initiation with phagophore formation by ATG9B, and elongation and maturation of autophagosome from phagophore through ATG12 and ATG8 system.\u003cstrong\u003e b-f) \u003c/strong\u003eDifferentiated THP-1 cells were pretreated with SAHA, 1uM, 24 hrs before infection with \u003cem\u003eA. baumannii\u003c/em\u003e for 2 hrs followed by 3 times PBS wash and further incubated for 4 hrs.\u003cstrong\u003e \u003c/strong\u003e\u0026nbsp;mRNA expression of genes such as ATG9B, ATG16L1, ATG5, ATG4C, and GABARAP which involved in the processes of autophagosome formation. Results were expressed in mean ± SEM. One-way ANOVA was used for statistical analysis with tukey’s multiple comparison test. \u003csup\u003e*\u003c/sup\u003ep \u0026lt; 0.05, \u003csup\u003e**\u003c/sup\u003ep \u0026lt; 0.01, and \u003csup\u003e***\u003c/sup\u003ep \u0026lt; 0.001. \u003cstrong\u003eg) \u003c/strong\u003eWestern blot of LC3-I to LC3-II conversion. β-actin was used as internal control. \u003cstrong\u003eh) \u003c/strong\u003eSchematic diagram of autophagosome-lysosome fusion process mediated by SNARE complex. \u003cstrong\u003ei-o) \u003c/strong\u003emRNA expression of SNARE proteins such as VAMP7, YKT6, STX17, and STX7, and SNAP proteins include SNAP25, SNAP29, and SNAP47. One-way ANOVA was used for statistical analysis with tukey’s multiple comparison test. \u003csup\u003e*\u003c/sup\u003ep \u0026lt; 0.05, \u003csup\u003e**\u003c/sup\u003ep \u0026lt; 0.01, and \u003csup\u003e***\u003c/sup\u003ep \u0026lt; 0.001. \u003cstrong\u003ep) \u003c/strong\u003eWestern blot of p62 level. β-actin was used as internal control.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7084777/v1/eccb4fd55ad9f24808a3a050.jpeg"},{"id":87001267,"identity":"974b2995-aade-4b8f-92ac-7a8590ce3f1a","added_by":"auto","created_at":"2025-07-18 07:22:07","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":782223,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSAHA increases autophagy flux by promoting autophagosome and lysosome fusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTHP-1 cells transduced with mCherry-GFP-LC3B construct were differentiated with 20ng/ml PMA for 24 hrs and treated cells with SAHA 1uM, 24 hrs before infection with \u003cem\u003eA. baumannii\u003c/em\u003e for 2 hrs followed by 3 times PBS wash and further incubated for 4 hrs. Autophagy activator (rapamycin, 500 nM, 24hrs) and autophagy inhibitors (chloroquine (20 µM, 24hrs) and bafilomycin A1 (20 nM, 24hrs)] were used as standards to evaluate the autophagy flux in terms of mCherry-LC3B/ GFP-LC3B ratio. \u003cstrong\u003ea)\u003c/strong\u003e Schematic diagram to understand the transition of autophagosome to autolysosome in THP-1 cells expressing mCherry-GFP-LC3B. Autophagosomes show both GFP and mCherry fluorescence (yellow – green), whereas autolysosomes exhibit only mCherry fluorescence (red color) because GFP is denatured in the presence of acidic condition of the lysosome. \u003cstrong\u003eb)\u003c/strong\u003e Representative fluorescent confocal images of THP-1 cells showing GFP-LC3B and mCherry-LC3B protein expression. Scale bar used is 5 µm \u003cstrong\u003ec)\u003c/strong\u003e Graphical representation of ratio of mCherry-LC3B/ GFP-LC3B fluorescence intensity between the groups. One-way ANOVA was used for statistical analysis with tukey’s multiple comparison test. \u003csup\u003e*\u003c/sup\u003ep \u0026lt; 0.05, \u003csup\u003e**\u003c/sup\u003ep \u0026lt; 0.01, and \u003csup\u003e***\u003c/sup\u003ep \u0026lt; 0.001. \u0026nbsp;\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7084777/v1/996dcbe1fa1e6d8f781e1bdb.png"},{"id":87002047,"identity":"9cac9263-6bb9-4da6-8a95-c55752d48c8d","added_by":"auto","created_at":"2025-07-18 07:30:07","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":544085,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRNA Seq data validation by qPCR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea) \u003c/strong\u003eHeatmap represents Z-score-based expression of DEGs (log fold change is 5, adjusted P value = 0.01). The Z-score was calculated using normalized gene expression value of RNAseq data.\u0026nbsp;\u0026nbsp; The blue color indicates the upregulation of genes (Z \u0026gt; 0), and the red color represents the downregulation of genes (Z \u0026lt; 0). \u003cstrong\u003eb-i)\u003c/strong\u003e mRNA expression of upregulated genes include, IDO1, ACOD1, IL10RA, IL10, TNF-α, IL6, IFNB1, and CCL3L3.\u0026nbsp; One-way ANOVA was used for statistical analysis with tukey’s multiple comparison test. \u003csup\u003e*\u003c/sup\u003ep \u0026lt; 0.05, \u003csup\u003e**\u003c/sup\u003ep \u0026lt; 0.01, and \u003csup\u003e***\u003c/sup\u003ep \u0026lt; 0.001. \u0026nbsp;\u003c/p\u003e","description":"","filename":"floatimage8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7084777/v1/c233295ab5ea10baf37cc35a.jpeg"},{"id":88846042,"identity":"edf9a1ce-482d-49d8-956c-789e885dd23e","added_by":"auto","created_at":"2025-08-12 04:01:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4534541,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7084777/v1/f27f8e08-1ae4-4afe-8597-5d93eff1a25e.pdf"},{"id":87002420,"identity":"494af605-bb34-4ee1-92ae-e2e1eebbb538","added_by":"auto","created_at":"2025-07-18 07:38:07","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":575467,"visible":true,"origin":"","legend":"","description":"","filename":"Supportinginformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-7084777/v1/b2f7300d06b9c710686990a5.docx"}],"financialInterests":"","formattedTitle":"SAHA Counteracts Host Response Alterations Driven by Carbapenem-Resistant Acinetobacter baumannii: A Transcriptomic Deep Dive","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHost-directed therapy (HDT) is a burgeoning approach for treating infectious diseases, it primarily focuses on host signaling pathways rather than acting upon the pathogens. The aim is to boost the host's defense mechanisms and mitigate pathogen-induced cell death while reducing the risk of anti-microbial resistance (AMR) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In the current scenario, AMR has become a global health threat, causing 1.2\u0026nbsp;million deaths yearly. With the lack of new antimicrobials, the death rate may rise to 10M per year by 2050 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Therefore, HDT serves as an alternative therapeutic option to tackle multidrug-resistant (MDR) pathogens by activating host defense mechanisms. Earlier reports showed that various pathogens learned to evade host defense mechanisms by altering the epigenetic machinery for their survival inside the host [\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDuring pathogen invasion, upregulation of histone deacetylase (HDACs) enzymes leads to host histone protein modification, which supports pathogen survival by decreasing the expression of host defense genes and inducing immunosuppression is mainly reported [\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In our previous study, we explored the regulation of histone acetylation in the THP-1 cell line infected with Carbapenem-resistant \u003cem\u003eA. baumannii\u003c/em\u003e (CRAB) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. CRAB is an opportunistic gram-negative bacteria responsible for nosocomial infectious diseases and also listed as a critical group pathogen in the global bacterial priority pathogen list (PPL) by the World Health Organization (WHO) [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. After infection with CRAB, we observed decreased acetylation levels of the histone proteins, H3K9ac, H3K27ac, and H2AK5ac and upregulation of five HDACs (HDAC1, HDAC4, HDAC6, HDAC7, and HDAC11) in THP-1 cells. Further, we used a pan-HDAC inhibitor-vorinostat (SAHA), to inhibit HDACs, which resulted in the restoration of histone acetylation levels and decreased survival of intracellular CRAB, previously [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFurther to delve into the mechanism by which SAHA treatment leads to reduced \u003cem\u003eCRAB\u003c/em\u003e burden and to identify the host transcripts involved in this modulation, we employed a comparative transcriptomic approach to investigate the host transcriptional changes. The present study will provide, for the first time, comprehensive insights into the host changes due to CRAB infection and highlight the potential of SAHA or HDAC inhibition in decreasing CRAB burden. This investigation will also shed light on the key host pathways, processes and genes involved in CRAB infection, identifying potential targets for HDT.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eThe host exhibits a plethora of gene modulation events in response to\u003c/b\u003e \u003cb\u003eA. baumannii\u003c/b\u003e \u003cb\u003einfection and SAHA treatment\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn the current study, we performed comparative RNA sequencing analysis among: i) AB-infected and uninfected control cells (AB vs C), ii) AB-infected cells with and without SAHA treatment (SAB vs AB) and iii) SAHA-treated cells with and without AB infection (SAB vs SC). Our transcriptomics analysis data revealed significant modulation of gene expression caused by AB, as well as in SAHA-treated AB-infected cells in comparison to their respective controls. We performed PCA to know the dynamic changes of gene expression in all groups and observed a positive correlation between the biological replicates of each group (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). Besides, we also used a hierarchical clustering heatmap to validate the correlation of gene expression in all pairwise combinations in groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). The PCA plot and hierarchical clustering heatmap showed a clear difference in gene expression in AB-infected and SAHA-treated groups.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFurther, we determined the complete DEGs profile of each group, in AB vs C, we found 1359 DEGs (845 upregulated and 514 downregulated), in SAB vs AB, 3850 DEGs (2032 upregulated and 1818 downregulated) and in SAB vs SC, 167 DEGs (162 upregulated and 5 downregulated) were observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). We also observed the common DEGs between the groups by plotting a Venn diagram (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). Interestingly, we found a reduced number of DEGs in the SAHA-treated group compared to the SAHA control, that implicit \u003cem\u003eA. baumannii\u003c/em\u003e could not regulate mRNA expression to survive in the SAHA pre-treated group. Moreover, we plotted a heatmap of all DEGs between the groups to observe the expression pattern of genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee).\u003c/p\u003e\u003cp\u003e\u003cb\u003eA. baumannii\u003c/b\u003e \u003cb\u003ecreates immunosuppressive conditions for its survival in the host\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFunctional analysis of DEGs between \u003cem\u003eAB\u003c/em\u003e and C was carried out to understand the modulations done by CRAB. Gene ontology (GO) revealed that most DEGs fell in the host's defensive mechanism against infection. We observed a few signaling biological processes showing high enrichment scores among all which included i) response to the virus, ii) response to lipopolysaccharide (LPS), iii) response to molecule of bacterial origin, and iv) defense response to the virus, which might contribute to tackling \u003cem\u003eA. baumannii\u003c/em\u003e in the early inflammatory phase (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). Further, we generated an emap plot to know the relations between the enriched biological processes. The biological process (\u0026ldquo;response to LPS\u0026rdquo;) has shown strong relationships with all processes that regulate the release of cytokines during AB infection (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). Later, we performed protein-protein interaction (PPI) network analysis by STRING database for the DEGs present in response to LPS biological process. It revealed that the genes were majorly involved in the TNF signaling pathway (KEGG ID: hsa04668, DEGs were highlighted in blue color) and IL10 signaling pathway (Reactome pathway ID: HSA-6783783, DEGs was highlighted in red color) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb), which have a connection with inflammatory-related genes and also responsible for immunosuppression in late infection stage [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The volcano plot analysis also showed that the genes IL10RA, IL6, TNF alpha, and IL1β were upregulated during AB infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Further, KEGG pathway analysis also showed the DEGs majorly involved in the inflammation-associated pathways, such as i) cytokine-cytokine receptor interaction (KEGG ID: hsa04060), ii) TNF signaling pathway (KEGG ID: hsa04668), and iii) NF-kappa B signaling pathway (KEGG ID: hsa04064), may have contributed to causing inflammation, which further progresses to sepsis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). Interestingly, we observed that cis-aconitate decarboxylase 1 (ACOD1) gene was upregulated in the \u003cem\u003eA. baumannii-infected\u003c/em\u003e group and have connection with pro-inflammatory cytokines such as IL6, TNF, and IL1β (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eSAHA allayed the transcriptional changes caused by\u003c/b\u003e \u003cb\u003eA. baumannii\u003c/b\u003e\u003c/p\u003e\u003cp\u003eLater, we analyzed the DEGs in SAB and observed decreased expression of pro-inflammatory cytokines (IL6 and TNFα), ACOD1 and IL10RA during infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Moreover, we also observed the upregulation of S100 family proteins such as S100A9 and S100A12 in the presence of SAHA, which are antimicrobial peptides that restrict the availability of metal ions to starve the bacteria [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. We also found that DEGs' highly enriched molecular function was tubulin binding (GO: 0015631) and microtubule binding (GO: 0008017) in the presence of SAHA (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). Next, we performed a KEGG pathway analysis that revealed phagosome (KEGG pathway ID: hsa04145) formation is the most enriched pathway in the presence of SAHA (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec), which is substantially related to other enriched pathways such as tuberculosis, leishmaniasis, and rheumatoid arthritis (\u003cb\u003eFigure S2\u003c/b\u003e). Besides, we plotted a heatmap of DEGs present in the phagosome KEGG pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed), and observed distinguished gene expression in SAHA-treated groups [SAHA control (SC) and infected\u0026thinsp;+\u0026thinsp;SAHA (SAB)] compared to infected (AB1 and AB2) and uninfected (C1 and C2), and network analysis of phagosome pathway also showed that the upregulation of tubulin binding proteins (TUBB3, TUBB2B, and TUBB4A) and major histocompatibility (MHC) class II proteins (HLA-DMA, HLA-DPA1, HLA-DMB, HLA-DQA1, and HLA-DQB1) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee), which regulates the formation of phagosome during bacterial infection and also antigen presentation and processing in MHC class II molecules that crucial for recruiting helper CD4\u0026thinsp;+\u0026thinsp;T cells to execute adaptive immunity [\u003cspan additionalcitationids=\"CR21 CR22\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Therefore, SAHA treatment leading to HDAC inhibition may have induced autophagy to kill \u003cem\u003eA. baumannii\u003c/em\u003e by upregulating S100A9 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef) and also decreasing the expression of ACOD1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eg).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eSAHA promotes S100A9-mediated autophagy to retard the survival of\u003c/b\u003e \u003cb\u003eA. baumannii\u003c/b\u003e \u003cb\u003eintracellularly\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe phagocytic effect of SAHA mainly depends on the upregulation of S100 family proteins such as S100A5 (\u003cb\u003eFigure S3a\u003c/b\u003e), calgranulin B (S100A9) (\u003cb\u003eFigure S3b\u003c/b\u003e), and calgranulin C (S100A12) (\u003cb\u003eFigure S3c\u003c/b\u003e), which limit the availability of essential metal ions (zinc, iron, and manganese) at infection foci to starve bacteria in a process called \u0026ldquo;nutritional immunity\u0026rdquo; [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Previous studies enlightened the role of antimicrobial peptides (S100A9 and S100A12) in the progression of autophagy to degrade intracellular bacteria and also in the restriction of bacterial invasion by inhibiting binding to the epithelial cells [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Therefore, we analyzed the effect of antimicrobial peptides on the autophagy process in the presence of SAHA during \u003cem\u003eA. baumannii\u003c/em\u003e infection. Initially, we looked into the expression of genes involved in the autophagosome formation, such as ATG9B (initiation- phagophore formation), ATG12 system (ATG16L1 and ATG5) and ATG8 system (ATG4C, LC3, and GABARAP) that are involved in the initiation, elongation and maturation of autophagosomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). SAHA treatment successfully activated autophagy by significantly upregulating ATG9B (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and ATG16L1 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), ATG5 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), ATG4C (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), GABARAP (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) compared to the infected group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb-\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ef). In addition, the conversion of LC3-I to LC3-II also increased in SAHA-treated groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eg \u0026amp; S4a). Further, we determined the expression of genes involved in the autophagosome and lysosome fusion process (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eh). Majorly, SNARE proteins (VAMP7, STX7, STX17, YKT6, and SNAP proteins such as SNAP25/29/47) present on the autophagosome and lysosome participate in the fusion process. We also observed significant increase of VAMP7, STX7, STX17, YKT6, and SNAP25/29/47 mRNA expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ei-\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eo), which promotes fusion process to eliminate \u003cem\u003eA. baumannii\u003c/em\u003e, also confirmed by the decreased of P62 level after autophagy completion (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ep \u0026amp; S4b). In addition, we used lentivirus transduction to introduce the mCherry-GFP-LC3B construct into THP-1 cells in order to monitor the fusion of autophagosomes with lysosomes \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea\u003cb\u003e)\u003c/b\u003e. The free autophagosomes contain both GFP-LC3B (green) and mCherry-LC3B (red), resulting in a yellow fluorescence (mCherry\u003csup\u003e+\u003c/sup\u003eGFP\u003csup\u003e+\u003c/sup\u003e). In contrast, autolysosomes display only red fluorescence (mCherry\u003csup\u003e+\u003c/sup\u003eGFP\u003csup\u003e\u0026minus;\u003c/sup\u003e), due to the degradation of GFP in the acidic lysosomal environment [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. To assess the fusion process, the ratio of mCherry-LC3B to GFP-LC3B fluorescence intensity was used. In this study, we observed that the ratio was reduced in the infected group and in cells treated with standard autophagy inhibitors (chloroquine and bafilomycin A1), suggesting an accumulation of autophagosomes (yellow: mCherry\u003csup\u003e+\u003c/sup\u003eGFP\u003csup\u003e+\u003c/sup\u003e) due to impaired fusion with lysosomes, in contrast to the increased ratio was observed in uninfected, SAHA and rapamycin (standard autophagy activator) treated groups \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec\u003cb\u003e)\u003c/b\u003e. Furthermore, we also observed that expression of LAMP3 was increased in \u003cem\u003eA. baumannii\u003c/em\u003e infected groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea). A recent study reported that high expression of LAMP3 inhibits autophagy through LAMP1 degradation by releasing cathepsin B and cathepsin D that activate caspase 1 and caspase 3 pathways [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. These findings suggest that \u003cem\u003eA. baumannii\u003c/em\u003e may evade host defenses by disrupting the autophagic process.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eRNA Seq data validation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe validated our RNA seq data using qPCR. The upregulated genes (IL6, TNFα, IFNB1, CCL3L3, IDO1, ACOD1, IL10, IL10RA) and downregulated genes (GPR65, HEY2, and SASH3) during \u003cem\u003eA. baumannii\u003c/em\u003e infection was selected. All the genes followed the same trend as observed in RNA seq.\u0026nbsp;As discussed in RNA-Seq data analysis, we observed a significant increase of ACOD1 in the \u003cem\u003eA. baumannii\u003c/em\u003e infected group, which is reportedly involved in the progression of sepsis. In the presence of SAHA, we found that the mRNA expression of IDO1, ACOD1, IL10RA, IL10, TNFα, IL6, IFNB1, and CCL3L3 genes was decreased during \u003cem\u003eA. baumannii\u003c/em\u003e infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb-\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ei). Further, validation of downregulated genes was performed, and decreased expression of GPR65, HEY2, and SASH3 was observed in \u003cem\u003eA. baumannii\u003c/em\u003e infected compared to uninfected (\u003cb\u003eFigure S5a-c\u003c/b\u003e). Here, we didn\u0026rsquo;t observe any changes in downregulated genes in the SAHA-treated group except the SASH3 gene, which showed a significant increase in the SAHA-treated group compared to the \u003cem\u003eA. baumannii-infected\u003c/em\u003e group.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the present study for the first time, we have attempted to showcase the pathways and genes modulated by \u003cem\u003eA. baumannii\u003c/em\u003e for its survival in the host. Especially, histone modifications which are the key regulators in innate immune defense response against bacterial invasion [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. However, bacteria employ various strategies to survive intracellularly by altering the status of histone acetylation level (H3K9ac and H3K27ac) and histone methylation level (H3K27me3) in the host that affects the transcription of immune defense genes [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Hence, we analyzed the transcriptomic data to find DEGs that regulates the survival of \u003cem\u003eA. baumannii\u003c/em\u003e in the presence of SAHA. SAHA treatment will increase histone acetylation levels by inhibiting HDACs and promoting transcription of immune defense genes [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. After infection, we didn\u0026rsquo;t observe any changes in the DEGs number in the infected\u0026thinsp;+\u0026thinsp;SAHA (SAB) group compared to SAHA control (SC) that denotes \u003cem\u003eA. baumannii\u003c/em\u003e was not able to alter the gene expression in presence of SAHA. Despite that, infected (AB) group showed a high number of DEGs in comparison to uninfected (C) group. Majorly, we seen inflammatory pathways such as cytokine-cytokine receptor interaction, TNF signaling pathway and NF-κB signaling pathways were enriched during infection, along with anti-inflammatory genes (e.g. IL10, IL10RA) that might contribute to sepsis. In addition, we also found that ACOD1 was upregulated in AB group compared to uninfected, which is reported to have a role in the sepsis progression. Previously, ACOD1 known as immune-responsive gene 1 (IRG1) which increases the production of itaconate, which exhibits antimicrobial and anti-inflammatory responses [\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. However, recent studies suggested that ACOD1 causes sepsis by exaggerating pro-inflammatory cytokines release through TLR4/NF-κB signaling pathway in \u003cem\u003eStaphylococcus aureus\u003c/em\u003e induces sepsis, CDK2/Jnu signaling and AGE-AGER pathway during cecal ligation and puncture (CLP) induced polymicrobial sepsis in mice [\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. ACOD1 deficiency increases the survival of mice and decreases pro-inflammatory response [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Therefore, ACOD1 could be a promising HDT target for treating \u003cem\u003eA. baumannii\u003c/em\u003e-induced septic conditions.\u003c/p\u003e\u003cp\u003eIn the presence of SAHA, the DEGs include IL6, TNF, IL10RA, and ACOD1 were downregulated, which denotes SAHA might restrict \u003cem\u003eA. baumannii\u003c/em\u003e persistence. In support of that, we observed that anti-microbial peptides (S100A9, S100A5, and S100A12) were upregulated and DEGs involved in the tubulin-binding and microtubules binding processes were highly enriched in SAHA treated group. In addition, KEGG pathway analysis revealed that the phagosome pathway is the highly enriched pathway in the presence of SAHA. The genes present in the phagosome pathway include i) tubulin binding proteins (TUBB3, TUBB2B, and TUBB4A), and ii) MHC class II proteins (HLA-DMA, HLA-DPA1, HLA-DMB, HLA-DQA1, and HLA-DQB1) were upregulated and also involved in the phagosome formation, antigen presenting and processing in MHC class II proteins containing vesicles. Several studies emphasized the role of anti-microbial peptides (S100A9 and S100A12), tubulin binding proteins in regulating autophagy and MHC class II molecules in antigen presentation and processing during bacterial infections [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. HDAC inhibition increases S100A9 and S100A12 level that induces autophagy process to increase clearance of \u003cem\u003eSalmonella enterica\u003c/em\u003e serovar Typhimurium intracellularly [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Therefore, we further examined the genes involved in the various phases of autophagy progression. First, we observed that ATG9B was significantly increased in SAHA treated group after \u003cem\u003eA. baumannii\u003c/em\u003e infection. Importantly, ATG9B is involved in the phagophore formation from the membrane, which is a crucial step for autophagosome formation. The deficiency of ATG9B suppresses the autophagy process [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Further, we have looked into the expression of ATG16L1, ATG5, ATG4C, LC3, and GABARAP genes which plays an important role in elongation and maturation of autophagosome [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Interestingly, ATG16L1 and ATG4C gene expression was decreased in infected group, while ATG16L1, ATG5, ATG4C and GABARAP was significantly upregulated in SAHA treated group after infection. Besides, we observed that SAHA treatment increases conversion of LC3-I to LC3-II, which is mediated by ATG4C expression.\u003c/p\u003e\u003cp\u003eTherefore, we concluded that SAHA induces autophagy by activating genes involved in i) initiation (ATG9B - phagophore formation), and ii) elongation and maturation (ATG16L1, ATG5, ATG4C, LC3, and GABARAP) of autophagosome formation. Previously, studies reported that SAHA induces autophagy by inhibiting HDACs [\u003cspan additionalcitationids=\"CR49 CR50\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Next, we investigated the effect of SAHA treatment on autophagosome and lysosome fusion process to hinder the \u003cem\u003eA. baumannii\u003c/em\u003e survival. The SNARE proteins (VAMP7, STX7, STX17, and YKT6) and SNAP proteins (SNAP25/29/47) plays a vital role in the fusion process [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. In this study, we observed increased level of VAMP7, STX7, STX17, YKT6 and SNAP25/29/47 in SAHA treated groups contributed to successful autophagosome-lysosome process. Importantly, STX7 and SNAP 29/47 expression was decreased in \u003cem\u003eA. baumannii\u003c/em\u003e infected group. Previous studies suggested that fusion is mediated by SNARE complexes, which forms a bridge between autophagosome and lysosome [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Mainly, two complexes such as STX17-SNAP29/47-VAMP7 and STX7-SNAP29/47-YKT6 were observed to mediate the fusion in the presence of SAHA to clear \u003cem\u003eA. baumannii\u003c/em\u003e intracellularly. Besides, P62 level was decreased in SAHA treated group, which indicates the completion of autophagosome and lysosome fusion. Our results suggested that \u003cem\u003eA. baumannii\u003c/em\u003e surviving inside the cells by inhibiting autophagosome-lysosome fusion indicated by increased p62 level. Lack of VAMP7 or ATG9B inhibits fusion process and accumulates p62 protein level [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. In addition, mCherry-LC3B /GFP-LC3B ratio was significantly decreased in AB infected group and in the presence of autophagy inhibitors (chloroquine and Bafilomycin A1) that clearly indicates the accumulation of autophagosomes (mCherry-GFP-LC3B: yellow color) and reduced fusion between the autophagosome and lysosome. In case of SAHA treatment and rapamycin, mCherry-LC3B /GFP-LC3B ratio was significantly increased which denotes completion of fusion and formation of autolysosome (mCherry-LC3B: red color) compared with AB infection. Several studies reported that the outer membrane proteins (OmpA, and Omp33-36) of \u003cem\u003eA. baumannii\u003c/em\u003e responsible for its persistence inside the host, which regulates CaMKK2-AMPK-ULK1 pathway, mTOR signaling pathway, and MAPK/JNK signaling pathways to inhibits autophagy process [\u003cspan additionalcitationids=\"CR58 CR59\" citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn conclusion, our results provide the understanding of mechanisms evaded by \u003cem\u003eA. baumannii\u003c/em\u003e through host histone modifications. Mainly, \u003cem\u003eA. baumannii\u003c/em\u003e hinders the autophagosome-lysosome fusion process to survive intracellularly. However, SAHA treatment activates autophagy and facilitates the fusion processes through important autophagy-related and SNARE proteins. Therefore, these findings demonstrate that HDAC inhibition by SAHA shows potential in decreasing bacterial survival by activating autophagy and immune pathways modulated during \u003cem\u003eA. baumannii\u003c/em\u003e infection.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cp\u003e\u003cb\u003eBacterial culture condition\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn this study, we used a CRAB clinical isolate (AB) obtained from ESIC hospital (Hyderabad, India), and the culture was maintained on a Mueller-Hinton agar (MHA) plate at 37\u003csup\u003eo\u003c/sup\u003eC.\u003c/p\u003e\u003cp\u003e\u003cb\u003eIntracellular macrophage infection\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTHP-1 cells were cultured in RPMI 1640 containing 10% v/v heat-inactivated fetal bovine serum (FBS), 100 IU/mL penicillin, 0.1mg/mL streptomycin, and 2mM L-glutamine at 37\u003csup\u003eo\u003c/sup\u003eC in 5% CO\u003csub\u003e2\u003c/sub\u003e. Cell differentiation was performed by adding phorbol-12-myristate-13-acetate (20ng/mL, PMA) for 24 hrs. The differentiated THP-1 cells (dTHP) were washed with fresh RPMI media and pretreated with SAHA (1\u0026micro;M) for 24 hrs. After SAHA treatment, cells were introduced to antibiotic-free RPMI media before infection with \u003cem\u003eA. baumannii\u003c/em\u003e for 2 hrs at a multiplicity of infection (MOI) 10, followed by three PBS washes to remove extracellular bacteria. The cells were then incubated for 4 hrs before performing RNA isolation.\u003c/p\u003e\u003cp\u003e\u003cb\u003eRNA isolation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTotal RNA was extracted using the TRIzol method, followed by DNase treatment to remove genomic DNA. The quality and quantity of the purified RNA were monitored using a nanodrop and bioanalyzer (RNA integrity number is \u0026gt;\u0026thinsp;9).\u003c/p\u003e\u003cp\u003e\u003cb\u003eRNA sequencing and data analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eLibrary preparation for RNA sequencing was done with Illumina-compatible NEBNext\u0026reg; Ultra\u0026trade; II Directional RNA Library Prep Kit (New England BioLabs, MA, USA) at Genotypic Technology Pvt. Ltd., Bangalore, India. 10ng-1ug of total RNA was used for mRNA isolation, fragmentation, and priming. Fragmented and primed mRNA was further subjected to first-strand synthesis followed by second-strand synthesis. The double-stranded cDNA was purified using NEBNext sample purification beads. Purified cDNA was end-repaired, adenylated, and ligated to Illumina adapters as per NEBNext\u0026reg; Ultra\u0026trade; II Directional RNA Library Prep protocol followed by second strand excision using USER\u003csup\u003e\u0026trade;\u003c/sup\u003e (Uracil-Specific Excision Reagent) enzyme at 37 ˚C for 15mins. Illumina universal adapters used in the study were: 5\u0026rsquo;AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCC\u003c/p\u003e\u003cp\u003eGATCT-3\u0026rsquo; and Index Adapter: 5\u0026rsquo;GATCGGAAGAGCACACGTCTGAACTCCAGTCAC\u003c/p\u003e\u003cp\u003eATCTCGTATGCCGTCTTCTGCTTG-3\u0026rsquo;. Adapter-ligated cDNA was purified using NEBNext beads and was subjected to 11 cycles for Indexing-(98˚C for 30 secs, cycling (98˚C for 10sec, 65˚C for 75sec) and 65˚C for 5min) and enriched the adapter-ligated fragments. Final PCR products (sequencing library) were purified with NEBNext beads, followed by a library quality control check. Illumina-compatible sequencing libraries were quantified by qubit fluorometer (Thermo Fisher Scientific, MA, USA), and fragment size distribution was analyzed on Agilent 2200 TapeStation.\u003c/p\u003e\u003cp\u003eRaw reads were processed by trimming adaptors and removing low-quality bases, dropping too short reads using trimmomatic-0.39. Later, the FASTQC tool was used to obtain the quality-filtered reads. The filtered reads were aligned to the reference genome human GRCh38 by HISAT2 and quantified by the feature counts tool [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. After quantification, the counts were used to obtain differentially expressed genes (DEGs) using DESeq2 in R studio [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. We performed sample-level quality control using principle component analysis (PCA) and hierarchical clustering to explore the similarity between the samples. Further, DEGs were plotted in Venn diagram using Venny 2.1 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bioinfogp.cnb.csic.es/tools/venny/index.html\u003c/span\u003e\u003cspan address=\"https://bioinfogp.cnb.csic.es/tools/venny/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), a volcano plot, a violin plot and gene enrichment analysis were generated by SRplot, and a heatmap was generated by pheatmap in R studio [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eQuantitative polymerase chain reaction (qPCR)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe validation of DEGs was performed using qPCR. Total RNA was extracted by using Nucleospin RNA kit (M-N) according to the manufacturer's instructions. Further, cDNA synthesis was done using Prime script 1st strand synthesis kit (Takara). 20ng of cDNA was used to perform qPCR using TB Green Premix Ex Taq II (Takara) in the QuantStudio 7 Pro instrument. GAPDH was used as the internal control. A list of primers used were given in \u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eWestern blotting\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAfter infection, cells were lysed by RIPA buffer containing protease inhibitor cocktail (cat no: ML051, Himedia) and centrifuged for 10mins at 10,000 rpm to collect supernatant. Later, the protein concentration in each group was quantified by bicinchoninic acid (BCA) assay kit (cat no: BCA1-1KT, Sigma Aldrich) and performed western blotting as described previously [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Briefly, Laemmli buffer was used to prepare the protein sample at 95\u003csup\u003eo\u003c/sup\u003eC for 10 mins in the presence of β-mercaptoethanol. Later, 40 \u0026micro;g of protein was run on SDS-PAGE gel followed by protein transfer on the PVDF membrane. The membrane was kept in blocking buffer (3% BSA) for 2 hrs after transfer and incubated with primary antibodies include LC3-I/II (cat no:12741S, CST) and P62 (cat no:18420-1-AP, ThermoFisher) overnight at 4\u003csup\u003eo\u003c/sup\u003eC. Later, the membrane was incubated with a secondary antibody (1:3000) at room temperature for 2 hrs after three washes with TBST buffer. Finally, the protein on the membrane was visualized in a chemidoc imaging system (Biorad) using enhanced chemiluminescence solution.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTransfection, lentivirus preparation and stable GFP-mCherry-LC3B cell preparation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eHEK293T cells were seeded in a 100mm petridish to reach 60\u0026ndash;70% confluency for the lentivirus preparation. Before transfection, cells were serum-starved for 1hr using Opti-MEM media. Lentiviral packaging psPAX2 (Addgene# 12260), enveloping plasmid PMD2.G (Addgene# 12259), GFP-mCherry-LC3B plasmid (Addgene # 170446) were mixed at a 4:2:1 ratio in Opti-MEM [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. Transfection was performed using the lipofectamine 3000 transfection kit (Thermofisher # L3000001). Briefly, DNA-P3000 and lipofectamine 3000 were mixed and co-transfected in HEK293T cells overnight for efficient transfection. Next day, cell media changed to DMEM high glucose with 20% FBS and incubated for an additional 48hr and 72hr virus secretion and harvesting. Cell supernatant containing virus particles was collected and passed through 0.45\u0026micro;M PES syringe filter to remove cellular parts and stored in -80 \u0026deg;c for further use. Later, THP-1 cell were seeded at 1x10\u003csup\u003e5\u003c/sup\u003e cells/well in 6 6-well plate and transduced with 500\u0026micro;l lentivirus soup and polybrene at 8\u0026micro;g/ml for 24hr. Cells were checked every day for GFP and mCherry expression as a stable insertion of the GFP-mCherry-LC3B plasmid into cells.\u003c/p\u003e\u003cp\u003e\u003cb\u003eImmunofluorescence\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAfter transfection, we differentiated THP-1 cells with PMA 20 ng/ml for 24 hrs followed by SAHA treatment for 24 hrs. Further, we infected SAHA treated cells with \u003cem\u003eA. baumannii\u003c/em\u003e for 2 hrs and washed with PBS, 3 times and incubated for 4 hrs. Autophagy activator (rapamycin, 500 nM, 24hrs) and autophagy inhibitors (chloroquine (20 \u0026micro;M, 24hrs) and bafilomycin A1 (20 nM, 24hrs) were used as standards to evaluate the autophagy flux in terms of mCherry-LC3B/ GFP-LC3B ratio. After infection, cells were fixed with 4% paraformaldehyde for 10mins and membrane permeabilization was done by 1% Triton-X 100 for 10 mins at RT. Further, cells were mounted with fluoromount-G with DAPI (cat no: 00-4959-52, Invitrogen) and images were taken by confocal microscope (Leica TCS SP8) at scale bar of 5 \u0026micro;m.\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eWe used GraphPad Prism V8 software to analyse statistical significance between the samples by applying one-way ANOVA with tukey\u0026rsquo;s multiple comparison test.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate: Not Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge the support of National Institute of Pharmaceutical Education and Research, Hyderabad, and Department of Pharmaceuticals (DoP), Ministry of Chemical and Fertilizer for conducting this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe part of the work was supported by the Indian Council of Medical Research (ICMR) IIRP-4907. S.S. thanks DoP for providing funding for this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRNA Seq data used in this study are available with BioProject Accession number PRJNA1276157.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Consent for publication:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have given consent for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone to declare\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSS: Conceptualised the idea, study design, performed the experiments, analysed the data, drafted and edited the manuscript. HMB and DV: Performed experiments, data analysis, and manuscript editing. HS and SKG: Performed transfection experiments. \u003cstrong\u003eRKB:\u0026nbsp;\u003c/strong\u003estudy supervision and manuscript editing\u003cstrong\u003e. VB:\u0026nbsp;\u003c/strong\u003eStudy design conceptualised the idea, supervision, resource arrangements, manuscript editing and finalisation of the draft.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Department of Biological Sciences, National Institute of Pharmaceutical Education and Research (NIPER), Hyderabad, Telangana \u0026ndash; 500037, India\u003cstrong\u003eSiva Singothu\u003csup\u003e1\u003c/sup\u003e, Harshala Maruti Baddi\u003csup\u003e1\u003c/sup\u003e, Divyasree Vulli\u003csup\u003e1\u003c/sup\u003e, Hoshiyar Singh\u003csup\u003e1\u003c/sup\u003e, Santosh Kumar Guru\u003csup\u003e1\u003c/sup\u003e, Vasundhra Bhandari\u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003e Department of General Medicine, ESIC Hospital, Sanath Nagar, Hyderabad, Telangana \u0026ndash; 500038, India\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRajiv Kumar Bandaru\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eShapira T, Christofferson M, Av-Gay Y. The antimicrobial activity of innate host-directed therapies: A systematic review. Int J Antimicrob Agents [Internet]. 2024;63:107138. Available from: https://www.sciencedirect.com/science/article/pii/S0924857924000566\u003c/li\u003e\n\u003cli\u003eNaghavi M, Vollset SE, Ikuta KS, Swetschinski LR, Gray AP, Wool EE, et al. Global burden of bacterial antimicrobial resistance 1990\u0026amp;#x2013;2021: a systematic analysis with forecasts to 2050. Lancet [Internet]. 2024;404:1199\u0026ndash;226. Available from: https://doi.org/10.1016/S0140-6736(24)01867-1\u003c/li\u003e\n\u003cli\u003eFol M, Włodarczyk M, Druszczyńska M. Host Epigenetics in Intracellular Pathogen Infections. Int. J. Mol. Sci. 2020. \u003c/li\u003e\n\u003cli\u003eThomas SS, Abhinand K, Menon AM, Nair BG, Kumar GB, Arun KB, et al. Epigenetic Mechanisms Induced by Mycobacterium tuberculosis to Promote Its Survival in the Host. Int. J. Mol. Sci. 2024. \u003c/li\u003e\n\u003cli\u003eRajeev R, Dwivedi AP, Sinha A, Agarwaal V, Dev RR, Kar A, et al. Epigenetic interaction of microbes with their mammalian hosts. J Biosci [Internet]. 2021;46:94. Available from: http://europepmc.org/abstract/MED/34728591\u003c/li\u003e\n\u003cli\u003eKavianFar A, Taherkhani H, Ahmadi A, Salimi M, Lanjanian H, Masoudi-Nejad A. Restoring the epigenetic landscape of lung microbiome: potential therapeutic approach for chronic respiratory diseases. BMC Pulm Med [Internet]. 2024;24:2. Available from: https://doi.org/10.1186/s12890-023-02789-7\u003c/li\u003e\n\u003cli\u003eHeim CE, Bosch ME, Yamada KJ, Aldrich AL, Chaudhari SS, Klinkebiel D, et al. Lactate production by Staphylococcus aureus biofilm inhibits HDAC11 to reprogramme the host immune response during persistent infection. Nat Microbiol. 2020;5:1271\u0026ndash;84. \u003c/li\u003e\n\u003cli\u003eBandyopadhaya A, Tsurumi A, Maura D, Jeffrey KL, Rahme LG. A quorum-sensing signal promotes host tolerance training through HDAC1-mediated epigenetic reprogramming. Nat Microbiol. 2016;1:1\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eSengupta S, Nayak B, Meuli M, Sander P, Mishra S, Sonawane A. Mycobacterium tuberculosis phosphoribosyltransferase promotes bacterial survival in macrophages by inducing histone hypermethylation in autophagy-related genes. Front Cell Infect Microbiol. 2021;11:676456. \u003c/li\u003e\n\u003cli\u003ePiatek P, Namiecinska M, Lewkowicz N, Kulińska-Michalska M, Jabłonowski Z, Matysiak M, et al. Histone H3 posttranslational modified enzymes defined neutrophil plasticity and their vulnerability to IL-10 in the course of the inflammation. J Inflamm. 2024;21:16. \u003c/li\u003e\n\u003cli\u003eSingothu S, Kinkar D, Vulli D, Brahma U, Bandaru RK, Bhandari V. Dysregulation of Host Histone Acetylation by Acinetobacter baumannii: A Novel Mechanism for Autophagy Inhibition and Bacterial Survival. ACS Infect Dis [Internet]. 2025; Available from: https://doi.org/10.1021/acsinfecdis.5c00080\u003c/li\u003e\n\u003cli\u003eAhuatzin-Flores OE, Torres E, Ch\u0026aacute;vez-Bravo E. Acinetobacter baumannii, a Multidrug-Resistant Opportunistic Pathogen in New Habitats: A Systematic Review. Microorganisms. 2024. \u003c/li\u003e\n\u003cli\u003eNguyen M, Joshi SG. Carbapenem resistance in Acinetobacter baumannii, and their importance in hospital‐acquired infections: a scientific review. J Appl Microbiol [Internet]. 2021;131:2715\u0026ndash;38. Available from: https://doi.org/10.1111/jam.15130\u003c/li\u003e\n\u003cli\u003eSati H, Carrara E, Savoldi A, Hansen P, Garlasco J, Campagnaro E, et al. The WHO Bacterial Priority Pathogens List 2024: a prioritisation study to guide research, development, and public health strategies against antimicrobial resistance. Lancet Infect Dis [Internet]. 2025; Available from: https://doi.org/10.1016/S1473-3099(25)00118-5\u003c/li\u003e\n\u003cli\u003eBen-Khemis M, Liu D, Pintard C, Song Z, Hurtado-Nedelec M, Marie J-C, et al. TNF\u0026alpha; counteracts interleukin-10 anti-inflammatory pathway through the NOX2-Lyn-SHP-1 axis in human monocytes. Redox Biol [Internet]. 2023;67:102898. Available from: https://www.sciencedirect.com/science/article/pii/S2213231723002999\u003c/li\u003e\n\u003cli\u003eCHAUDHRY H, ZHOU J, ZHONG YIN, ALI MIRM, MCGUIRE F, NAGARKATTI PS, et al. Role of Cytokines as a Double-edged Sword in Sepsis. In Vivo (Brooklyn) [Internet]. 2013;27:669 LP \u0026ndash; 684. Available from: http://iv.iiarjournals.org/content/27/6/669.abstract\u003c/li\u003e\n\u003cli\u003eFriedman G, Jankowski S, Marchant A, Goldman M, Kahn RJ, Vincent JL. Blood interleukin 10 levels parallel the severity of septic shock. J Crit Care [Internet]. 1997;12:183\u0026ndash;7. Available from: https://www.sciencedirect.com/science/article/pii/S0883944197900307\u003c/li\u003e\n\u003cli\u003eKozlyuk N, Monteith AJ, Garcia V, Damo SM, Skaar EP, Chazin WJ. S100 Proteins in the Innate Immune Response to Pathogens BT - Calcium-Binding Proteins of the EF-Hand Superfamily: From Basics to Medical Applications. In: Heizmann CW, editor. New York, NY: Springer New York; 2019. p. 275\u0026ndash;90. Available from: https://doi.org/10.1007/978-1-4939-9030-6_18\u003c/li\u003e\n\u003cli\u003eZackular JP, Chazin WJ, Skaar EP. Nutritional Immunity: S100 Proteins at the Host-Pathogen Interface *. J Biol Chem [Internet]. 2015;290:18991\u0026ndash;8. Available from: https://doi.org/10.1074/jbc.R115.645085\u003c/li\u003e\n\u003cli\u003eLigeon L-A, Pena-Francesch M, Vanoaica LD, N\u0026uacute;\u0026ntilde;ez NG, Talwar D, Dick TP, et al. Oxidation inhibits autophagy protein deconjugation from phagosomes to sustain MHC class II restricted antigen presentation. Nat Commun [Internet]. 2021;12:1508. Available from: https://doi.org/10.1038/s41467-021-21829-6\u003c/li\u003e\n\u003cli\u003eSanta K. Macrophages: Phagocytosis, Antigen Presentation, and Activation of Immunity. In: Athari SS, Nasab EM, editors. Rijeka: IntechOpen; 2023. Available from: https://doi.org/10.5772/intechopen.110832\u003c/li\u003e\n\u003cli\u003eDuraes F V, Niven J, Dubrot J, Hugues S, Gannag\u0026eacute; M. Macroautophagy in Endogenous Processing of Self- and Pathogen-Derived Antigens for MHC Class II Presentation. Front Immunol [Internet]. 2015;Volume 6-. Available from: https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2015.00459\u003c/li\u003e\n\u003cli\u003eRoche PA, Furuta K. The ins and outs of MHC class II-mediated antigen processing and presentation. Nat Rev Immunol [Internet]. 2015;15:203\u0026ndash;16. Available from: https://doi.org/10.1038/nri3818\u003c/li\u003e\n\u003cli\u003eSchulthess J, Pandey S, Capitani M, Rue-Albrecht KC, Arnold I, Franchini F, et al. The short chain fatty acid butyrate imprints an antimicrobial program in macrophages. Immunity. 2019;50:432-445. e7. \u003c/li\u003e\n\u003cli\u003eKanokwan N, F. RK, C. HM. Calprotectin Expression Inhibits Bacterial Binding to Mucosal Epithelial Cells. Infect Immun [Internet]. 2001;69:3692\u0026ndash;6. Available from: https://doi.org/10.1128/iai.69.6.3692-3696.2001\u003c/li\u003e\n\u003cli\u003eChampaiboon C, Sappington KJ, Guenther BD, Ross KF, Herzberg MC. Calprotectin S100A9 Calcium-binding Loops I and II Are Essential for Keratinocyte Resistance to Bacterial Invasion *. J Biol Chem [Internet]. 2009;284:7078\u0026ndash;90. Available from: https://doi.org/10.1074/jbc.M806605200\u003c/li\u003e\n\u003cli\u003eKim S, Choi S, Kang D. Quantitative and qualitative analysis of autophagy flux using imaging. BMB Rep [Internet]. 2020/05/31. 2020;53:241\u0026ndash;7. Available from: https://www.bmbreports.org/journal/view.html?doi=10.5483/BMBRep.2020.53.5.046\u003c/li\u003e\n\u003cli\u003eTanaka T, Blake M. W, Drew G. M, Hiroyuki N, Toshio O, Hongen Y, et al. LAMP3 inhibits autophagy and contributes to cell death by lysosomal membrane permeabilization. Autophagy [Internet]. 2022;18:1629\u0026ndash;47. Available from: https://doi.org/10.1080/15548627.2021.1995150\u003c/li\u003e\n\u003cli\u003eLi X, Ye Y, Peng K, Zeng Z, Chen L, Zeng Y. Histones: The critical players in innate immunity. Front Immunol [Internet]. 2022;Volume 13. Available from: https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2022.1030610\u003c/li\u003e\n\u003cli\u003eHamon MA, Cossart P. Histone Modifications and Chromatin Remodeling during Bacterial Infections. Cell Host Microbe [Internet]. 2008;4:100\u0026ndash;9. Available from: https://www.sciencedirect.com/science/article/pii/S193131280800228X\u003c/li\u003e\n\u003cli\u003eLin Y, Qiu T, Wei G, Que Y, Wang W, Kong Y, et al. Role of Histone Post-Translational Modifications in Inflammatory Diseases. Front Immunol [Internet]. 2022;Volume 13. Available from: https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2022.852272\u003c/li\u003e\n\u003cli\u003eWu D, Shi Y, Zhang H, Miao C. Epigenetic mechanisms of Immune remodeling in sepsis: targeting histone modification. Cell Death Dis [Internet]. 2023;14:112. Available from: https://doi.org/10.1038/s41419-023-05656-9\u003c/li\u003e\n\u003cli\u003eXu T, Fang Y, Gu Y, Xu D, Hu T, Yu T, et al. HDAC inhibitor SAHA enhances antitumor immunity via the HDAC1/JAK1/FGL1 axis in lung adenocarcinoma. J Immunother Cancer [Internet]. 2024;12:e010077. Available from: http://jitc.bmj.com/content/12/10/e010077.abstract\u003c/li\u003e\n\u003cli\u003eLi R, Zhang P, Wang Y, Tao K. Itaconate: A Metabolite Regulates Inflammation Response and Oxidative Stress. Oxid Med Cell Longev [Internet]. 2020;2020:5404780. Available from: https://doi.org/10.1155/2020/5404780\u003c/li\u003e\n\u003cli\u003eCoelho C. Itaconate or how I learned to stop avoiding the study of immunometabolism. PLOS Pathog [Internet]. 2022;18:e1010361. Available from: https://doi.org/10.1371/journal.ppat.1010361\u003c/li\u003e\n\u003cli\u003eAl Akiki Dit Al Mazraani R, Malys N, Maliene V. Itaconate and its derivatives as anti-pathogenic agents. RSC Adv [Internet]. 2025;15:4408\u0026ndash;20. Available from: http://dx.doi.org/10.1039/D4RA08298B\u003c/li\u003e\n\u003cli\u003eDai F, Zhang X, Ma G, Li W. ACOD1 mediates Staphylococcus aureus-induced inflammatory response via the TLR4/NF-\u0026kappa;B signaling pathway. Int Immunopharmacol [Internet]. 2024;140:112924. Available from: https://www.sciencedirect.com/science/article/pii/S1567576924014450\u003c/li\u003e\n\u003cli\u003eBai L, Yu H, Cai Y, Wu R, Kang R, Jia Y, et al. Itaconate drives pro-inflammatory responses through proteasomal degradation of GLO1. Biochem Biophys Res Commun [Internet]. 2025;747:151292. Available from: https://www.sciencedirect.com/science/article/pii/S0006291X25000063\u003c/li\u003e\n\u003cli\u003eWu R, Liu J, Wang N, Zeng L, Yu C, Chen F, et al. Aconitate decarboxylase 1 is a mediator of polymicrobial sepsis. Sci Transl Med [Internet]. 2025;14:eabo2028. Available from: https://doi.org/10.1126/scitranslmed.abo2028\u003c/li\u003e\n\u003cli\u003eTomlinson KL, Riquelme SA, Baskota SU, Drikic M, Monk IR, Stinear TP, et al. Staphylococcus aureus stimulates neutrophil itaconate production that suppresses the oxidative burst. Cell Rep [Internet]. 2023;42:112064. Available from: https://www.sciencedirect.com/science/article/pii/S221112472300075X\u003c/li\u003e\n\u003cli\u003eK\u0026ouml;chl R, Hu XW, Chan EYW, Tooze SA. Microtubules Facilitate Autophagosome Formation and Fusion of Autophagosomes with Endosomes. Traffic [Internet]. 2006;7:129\u0026ndash;45. Available from: https://doi.org/10.1111/j.1600-0854.2005.00368.x\u003c/li\u003e\n\u003cli\u003eXia P, Ji X, Yan L, Lian S, Chen Z, Luo Y. Roles of S100A8, S100A9 and S100A12 in infection, inflammation and immunity. Immunology [Internet]. 2024;171:365\u0026ndash;76. Available from: https://doi.org/10.1111/imm.13722\u003c/li\u003e\n\u003cli\u003eCrotzer VL, Blum JS. Autophagy and Its Role in MHC-Mediated Antigen Presentation1. J Immunol [Internet]. 2009;182:3335\u0026ndash;41. Available from: https://doi.org/10.4049/jimmunol.0803458\u003c/li\u003e\n\u003cli\u003eGhavami S, Eshragi M, Ande SR, Chazin WJ, Klonisch T, Halayko AJ, et al. S100A8/A9 induces autophagy and apoptosis via ROS-mediated cross-talk between mitochondria and lysosomes that involves BNIP3. Cell Res [Internet]. 2010;20:314\u0026ndash;31. Available from: https://doi.org/10.1038/cr.2009.129\u003c/li\u003e\n\u003cli\u003eWang N, Tan H-Y, Li S, Feng Y. Atg9b deficiency suppresses autophagy and potentiates endoplasmic reticulum stress-associated hepatocyte apoptosis in hepatocarcinogenesis. Theranostics. 2017;7:2325. \u003c/li\u003e\n\u003cli\u003eNoda T, Fujita N, Yoshimori T. The late stages of autophagy: how does the end begin? Cell Death Differ [Internet]. 2009;16:984\u0026ndash;90. Available from: https://doi.org/10.1038/cdd.2009.54\u003c/li\u003e\n\u003cli\u003eZhao YG, Codogno P, Zhang H. Machinery, regulation and pathophysiological implications of autophagosome maturation. Nat Rev Mol Cell Biol. 2021;22:733\u0026ndash;50. \u003c/li\u003e\n\u003cli\u003eYang J, He J, Ismail M, Tweeten S, Zeng F, Gao L, et al. HDAC inhibition induces autophagy and mitochondrial biogenesis to maintain mitochondrial homeostasis during cardiac ischemia/reperfusion injury. J Mol Cell Cardiol [Internet]. 2019;130:36\u0026ndash;48. Available from: https://doi.org/10.1016/j.yjmcc.2019.03.008\u003c/li\u003e\n\u003cli\u003eFr\u0026ouml;hlich LF, Mrakovcic M, Smole C, Zatloukal K. Molecular mechanism leading to SAHA-induced autophagy in tumor cells: Evidence for a p53-dependent pathway. Cancer Cell Int. 2016;16:1\u0026ndash;15. \u003c/li\u003e\n\u003cli\u003eFoggetti G, Ottaggio L, Russo D, Mazzitelli C, Monti P, Degan P, et al. Autophagy induced by SAHA affects mutant P53 degradation and cancer cell survival. Biosci Rep [Internet]. 2019;39:BSR20181345. Available from: https://doi.org/10.1042/BSR20181345\u003c/li\u003e\n\u003cli\u003eLee JY-C, Kuo C-W, Tsai S-L, Cheng SM, Chen S-H, Chan H-H, et al. Inhibition of HDAC3- and HDAC6-Promoted Survivin Expression Plays an Important Role in SAHA-Induced Autophagy and Viability Reduction in Breast Cancer Cells. Front Pharmacol [Internet]. 2016;Volume 7-. Available from: https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2016.00081\u003c/li\u003e\n\u003cli\u003eHikita H, Sakane S, Takehara T. Mechanisms of the autophagosome-lysosome fusion step and its relation to non-alcoholic fatty liver disease. Liver Res [Internet]. 2018;2:120\u0026ndash;4. Available from: https://www.sciencedirect.com/science/article/pii/S2542568418300254\u003c/li\u003e\n\u003cli\u003eJian F, Wang S, Tian R, Wang Y, Li C, Li Y, et al. The STX17-SNAP47-VAMP7/VAMP8 complex is the default SNARE complex mediating autophagosome\u0026ndash;lysosome fusion. Cell Res. 2024;34:151\u0026ndash;68. \u003c/li\u003e\n\u003cli\u003eZheng D, Tong M, Zhang S, Pan Y, Zhao Y, Zhong Q, et al. Human YKT6 forms priming complex with STX17 and SNAP29 to facilitate autophagosome-lysosome fusion. Cell Rep [Internet]. 2024;43:113760. Available from: https://www.sciencedirect.com/science/article/pii/S2211124724000883\u003c/li\u003e\n\u003cli\u003eChoi J, Haeun J, Zhao X, and Park D. Emerging roles of ATG9/ATG9A in autophagy: implications for cell and neurobiology. Autophagy [Internet]. 2024;20:2373\u0026ndash;87. Available from: https://doi.org/10.1080/15548627.2024.2384349\u003c/li\u003e\n\u003cli\u003eAoyagi K, Ohara-Imaizumi M, Itakura M, Torii S, Akimoto Y, Nishiwaki C, et al. VAMP7 regulates autophagy to maintain mitochondrial homeostasis and to control insulin secretion in pancreatic \u0026beta;-cells. Diabetes. 2016;65:1648\u0026ndash;59. \u003c/li\u003e\n\u003cli\u003eKyungho W, Ho KD, Ho-Sung P, Hwan OM, Chul LJ, Hee CC. Acinetobacter baumannii OmpA hinders host autophagy via the CaMKK2-reliant AMPK-pathway. MBio [Internet]. 2025;16:e03369-24. Available from: https://doi.org/10.1128/mbio.03369-24\u003c/li\u003e\n\u003cli\u003eCarlos R, Mar\u0026iacute;a T, Esteban FM, Cruz SN, Micaela C, Elena S, et al. The Acinetobacter baumannii Omp33-36 Porin Is a Virulence Factor That Induces Apoptosis and Modulates Autophagy in Human Cells. Infect Immun [Internet]. 2014;82:4666\u0026ndash;80. Available from: https://doi.org/10.1128/iai.02034-14\u003c/li\u003e\n\u003cli\u003eZhao D, Li Y, Peng C, Lin J, Yu F, Zhao Y, et al. Outer membrane protein a in Acinetobacter baumannii induces autophagy through mTOR signalling pathways in the lung of SD rats. Biomed Pharmacother [Internet]. 2021;135:111034. Available from: https://www.sciencedirect.com/science/article/pii/S0753332220312269\u003c/li\u003e\n\u003cli\u003eAn Z, Huang X, Zheng C, Ding W. Acinetobacter baumannii outer membrane protein A induces HeLa cell autophagy via MAPK/JNK signaling pathway. Int J Med Microbiol. 2019;309:97\u0026ndash;107. \u003c/li\u003e\n\u003cli\u003eKim D, Paggi JM, Park C, Bennett C, Salzberg SL. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat Biotechnol [Internet]. 2019;37:907\u0026ndash;15. Available from: https://doi.org/10.1038/s41587-019-0201-4\u003c/li\u003e\n\u003cli\u003eLiao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics [Internet]. 2014;30:923\u0026ndash;30. Available from: https://doi.org/10.1093/bioinformatics/btt656\u003c/li\u003e\n\u003cli\u003eLove MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol [Internet]. 2014;15:550. Available from: https://doi.org/10.1186/s13059-014-0550-8\u003c/li\u003e\n\u003cli\u003eTang D, Chen M, Huang X, Zhang G, Zeng L, Zhang G, et al. SRplot: A free online platform for data visualization and graphing. PLoS One [Internet]. 2023;18:e0294236. Available from: https://doi.org/10.1371/journal.pone.0294236\u003c/li\u003e\n\u003cli\u003eBabu SSN, Singla S, Jena G. Role of combination treatment of aspirin and zinc in DMH-DSS-induced colon inflammation, oxidative stress and tumour progression in male BALB/c mice. Biol Trace Elem Res. 2023;201:1327\u0026ndash;43. \u003c/li\u003e\n\u003cli\u003eWulansari N, Darsono WHW, Woo H-J, Chang M-Y, Kim J, Bae E-J, et al. Neurodevelopmental defects and neurodegenerative phenotypes in human brain organoids carrying Parkinson\u0026rsquo;s disease-linked DNAJC6 mutations. Sci Adv [Internet]. 2025;7:eabb1540. Available from: https://doi.org/10.1126/sciadv.abb1540\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Transcriptomics, Acinetobacter baumannii, Histone protein modifications, Autophagy, and Host-directed therapy","lastPublishedDoi":"10.21203/rs.3.rs-7084777/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7084777/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBacterial pathogens remodel the host epigenetic programming to surpass host defence mechanisms for their benefit. The studies on carbepenem-resistant \u003cem\u003eA. baumannii\u003c/em\u003e (CRAB) circumvention of host defence mechanisms, especially the role of host HDAC inhibition on its survival, have not been investigated. In the current study, we employed comparative transcriptomics to investigate changes in the key host pathways and biological processes during \u003cem\u003eA. baumannii\u003c/em\u003e infection and after its treatment with SAHA (pan HDAC inhibitor). Our primary findings highlighted that \u003cem\u003eA. baumannii\u003c/em\u003e establishes an immunosuppressive condition by regulating both TNFα and IL10 signaling pathways for its persistence. We found overexpression of the ACOD1 gene during infection, which is reportedly involved in the progression of sepsis. In the presence of SAHA, the mRNA expression of IDO1, ACOD1, IL10RA, IL10, TNFα, IL6, IFNB1, and CCL3L3 genes was found to be decreased during AB infection. Further, we observed that SAHA treatment induces autophagy by regulating the genes involved in phagosome maturation and antigen processing through tubulin binding and MHC class II proteins, respectively. Moreover, SAHA facilitates the autophagosome-lysosome fusion process through upregulation of important autophagy-related and SNARE proteins, causing bacterial clearance. Therefore, our findings provide a comprehensive insight into the \u003cem\u003eA. baumannii\u003c/em\u003e immune evasion mechanisms and the potential of SAHA as a host-directed therapeutic against \u003cem\u003eA. baumannii\u003c/em\u003e infection.\u003c/p\u003e","manuscriptTitle":"SAHA Counteracts Host Response Alterations Driven by Carbapenem-Resistant Acinetobacter baumannii: A Transcriptomic Deep Dive","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-18 07:22:02","doi":"10.21203/rs.3.rs-7084777/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0b0c8dcb-41b7-4c0f-94a4-e378079d7bf8","owner":[],"postedDate":"July 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-12T03:53:39+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-18 07:22:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7084777","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7084777","identity":"rs-7084777","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}