Circadian Clock protein Bmal1 drives inflammatory homing in monocytes via augmented Cxcr4 and Ccr2 axis

Circadian Clock protein Bmal1 drives inflammatory homing in monocytes via augmented Cxcr4 and Ccr2 axis | 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 Article Circadian Clock protein Bmal1 drives inflammatory homing in monocytes via augmented Cxcr4 and Ccr2 axis Ranjitsinh Devkar, Rhydham Karnik, Helly Shah, Aliasgar Vohra, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8894070/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 Chronodisruption from shift work or sleep disruption is associated with inflammatory diseases, but the molecular pathways linking circadian disruption to aberrant immune cell trafficking remain unclear. Here, we identify a circadian-immune circuit wherein the core clock protein BMAL1 regulates monocyte homing by controlling chemokine receptors CXCR4 and CCR2. In sleep-disrupted individuals, we observed elevated monocyte counts alongside increased BMAL1 and chemokine receptor expression. Using a physiologically relevant murine model of chronic chronodisruption, we found that BMAL1 upregulation alters the diurnal rhythm of monocyte trafficking, leading to aberrant splenic retention and amplified chemokine-driven migratory signaling. ChIP-seq analysis revealed BMAL1 occupancy at enhancer regions of Cxcr4 and Ccr2, and its knockdown significantly attenuated their expression and associated PI3K–CDC42/RAC1 signaling. Adoptively transferred monocytes from chronodisrupted mice showed no trafficking abnormalities in healthy recipients but displayed a biased migratory preference for inflamed liver tissue upon inflammatory challenge. Our findings identify the BMAL1–chemokine axis as a regulator of monocyte trafficking and provide a mechanistic basis for heightened inflammatory responses under conditions of circadian disruption. Biological sciences/Immunology/Chemokines Biological sciences/Immunology/Innate immune cells/Monocytes and macrophages Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Main The circadian clock is an evolutionarily conserved, cell-autonomous transcriptional-translational feedback loop (TTFL) that orchestrates ~ 24-hour rhythms in physiology and gene expression, synchronizing cellular processes with the light-dark cycle. Core clock proteins, including BMAL1 and CLOCK, drive the rhythmic expression of clock-controlled genes (CCGs), which regulate diverse functions from metabolism to immune responses.( 1 ) In the immune system, a temporal regulation is not merely a passive response, but an active anticipatory program that gates processes such as leukocyte circulation, cytokine release and antimicrobial defence. Disruption of this finely tuned temporal order (chronodisruptiuon; CD) is a pervasive feature of modern life and a significant contributor to chronic disease.( 2 ) It results from environmental insults such as shift work, chronic jet lag and sleep disorders.( 3 , 4 ) This disruption is a hallmark and exacerbating factor in a range of conditions including cardiometabolic disorders, autoimmune diseases, and neuroinflammation.( 5 , 6 ) Non-Alcoholic Fatty Liver Disease (NAFLD), rheumatoid arthritis or cancer furthers disease progression through ill-defined inflammatory pathways and by triggering a vicious cycle that furthers sleep disturbances and nocturnal wakefulness leading to CD.( 7 , 8 ) A cardinal feature of this circadian-immune interface is the regulation of myeloid cell trafficking.( 9 ) Monocytes are the key mediators of innate immunity and tissue homeostasis that exhibit robust diurnal oscillations in their release from the bone marrow and their recruitment to tissues.( 10 ) This homing is governed by the rhythmic expression of chemokine receptors, notably CCR2 and CXCR4, that respond to spatial gradients of their ligands (e.g., CCL2, CXCL12).( 11 ) Under circadian control, this system ensures precise temporal delivery of monocytes and balancing immune surveillance by preventing excessive tissue inflammation. When this temporal gating fails, the consequences are profound. ( 10 , 12 ) Aberrant, non-rhythmic monocyte infiltration into tissues is a key driver of the low-grade, persistent inflammation that characterizes metabolic syndrome and atherosclerosis.( 13 ) In conditions like psoriasis and inflammatory bowel disease, inappropriate leukocyte recruitment directly contributes to lesion formation and flare-ups.( 14 , 15 ) The nocturnal influx of inflammatory monocytes into tissues, if mistimed or excessive, can shift a protective immune response toward a pathogenic, tissue-destructive state.( 16 , 17 ) Despite this clear link, the precise molecular mechanism by which the core circadian clock directly governs the chemotactic machinery of monocytes—and how this mechanism breaks down in disease—remains a critical and unresolved question. Previous attempts to define this link have relied heavily on global or myeloid-specific knockout mice models, representing an extreme of circadian dysfunction (complete loss) rather than the dysregulation (altered amplitude or timing) synonymous with the human diseases. This gap has left a fundamental unanswered question on how the pathological upregulation or mistiming of core clock components directly reprogram monocyte homing and promote inflammation. In this study, we address this gap by testing the hypothesis that core clock protein BMAL1 may regulate the transcription of chemokine receptors (CXCR4 and CCR2). Using a translational approach, we integrate the data from sleep-disrupted human cohort, a murine model of shift work and in vitro studies. Taken together, we report on consequences of chronic sleep disruption as a core regulator of rhythmic monocyte trafficking via a novel BMAL1-chemokine receptor axis. This axis accounts for an aberrant tissue homing of monocytes that may have far reaching consequences in metabolic and immune disorders. Results Sleep deprivation is associated with altered monocyte numbers and core clock gene expression in humans We studied the complete blood count (CBC) of healthy (Control) and Sleep disrupted (CD) individuals segregated as per our circulated questionaries (Supplementary Table 1, 3) to assess possible manifestations of altered sleep-wakefulness cycle in circulation. Individuals reporting long-term irregular sleep patterns, including consistent late-night work shifts, habitual sleep onset after 23:00, and weekday-to-weekday sleep timing variability (> 2-hour difference on ≥ 3 days/week), were classified as the Sleep Disrupted (CD) group.( 18 , 19 ). Next, we undertook complete blood count at two different timepoints to understand implications of sleep irregularities in circulating leukocyte levels. Blood was collected from Control and CD individuals as per Helsinki Declaration from Morning (9 AM to 11AM) and Evening (7 PM to 9 PM) (Fig. 1 A). Complete blood count analysis revealed a significant increase in circulating monocytes in CD individuals (mean ± SD, 1.2 vs 2.5 x 10 5 cells/mL; p < 0.0001, unpaired t-test), accompanied by reduced total WBC (p < 0.05) and lymphocyte counts (p < 0.001) (Fig. 1 B). Next, we compared the differential increase in leukocyte number from morning to evening timepoints. Differential monocyte counts exhibited a disrupted morning-to-evening variation in CD individuals (p < 0.001), indicating altered diurnal distribution (Fig. 1 C). These changes are subtle and warrant a deeper investigation into the transcriptomic signature to decode the role of circadian regulators in monocyte trafficking. Monocytes rely on the dynamic expression of chemokine receptors for their trafficking and circulation. Monocytes that are isolated from blood are sensitive to external stimuli and differentiate into monocyte derived macrophages. Therefore, we isolated untouched monocytes that are pure, label free and versatile for gene expression. Chemokine receptors (CXCR4 (p < 0.001) & CCR2) and clock gene (BMAL1 (p < 0.05) & CLOCK (p < 0.0001)) revealed a significantly lower expression in control volunteers as compared to CD after normalization with Actin protein expression (Fig. 1 D, E). Perturbations in circulating monocytes are regulated by chemokine receptors and our results further indicate a clear association between chemokine and Bmal1 downregulation in control volunteers (Fig. 1 D, E). However, these changes were preliminary observations in self-reported sleep disturbed individual that are hypothesis generating and warranted a deeper investigation. We acknowledge several limitations of the human data. First, the sample size (n = 20) is modest, and the findings should be considered preliminary. Second, sleep disruption was assessed by self-report rather than objective measures such as actigraphy, which may introduce reporting bias. Third, the observed correlations do not establish causality. Larger, longitudinal studies with objective sleep monitoring are needed to validate these findings. $$\:Differnetial\:Monocyte\:Count=Evening\:Mono.\:Counts-Morning\:Mono.\:Counts$$ Circadian desynchrony disrupts the monocyte trafficking in mice We had examined whether diurnal oscillations in monocyte trafficking were altered due to Chronodisruption in C57BL/6J mice. The diurnal trafficking of CD11b + lymphocytes, CD11b + Ly6C − non-classical monocytes and CD11b + Ly6C + classical monocytes was evaluated to understand the homeostatic myeloid release of immune cells from bone marrow into blood in CD. Monocytes from myeloid compartments (blood, bone marrow and spleen) were isolated from control and CD mice (n = 3 per timepoint per group) at 5 intervals (ZT0, 6, 12, 18 and 24) during 24hrs. Food intake, water intake and body weight were recorded during the CD protocol and organ weight was taken post euthanasia and liver histology was performed (Fig. 1 Extended Data 1D, E)Diurnal changes in myeloid compartments were analyzed using flow cytometry (Fig. 2 A). Gating strategy for each of the key compartment is given in extended data (Fig. 1 Extended Data 1A-C). Chronodisruption induced a measurable phase shift in the diurnal oscillations of CD11b⁺ lymphocytes and CD11b⁺Ly6C⁻ non-classical monocytes, shifting peak abundance from the inactive to the active phase across bone marrow, blood, and spleen (Fig. 3 B–E). Bone marrow monocyte abundance showed no significant difference between groups (p > 0.05, two-way ANOVA) (Fig. 3 B, D). Homeostatic myeloid release of Ly6C + monocytes from bone marrow was observed at ZT6 which is in consensus with activity period of mice and already published literature. Ly6C + monocytes percentage peaked in bone marrow during the active period (ZT12-ZT24) in control mice whereas; in CD mice a single peak was recorded at ZT 18 (p < 0.05) (Fig. 3 B, D). Our results demonstrate a consistent increment (ZT12-ZT18) in Blood Ly6C + monocytes percentage of CD mice as compared to a single peak at ZT12 in control (Fig. 3 B, C). Consinor analysis was performed to quantify the amplitude and peak time. Similar observations were recorded wherein Ly6C + monocytes shown a peak shift (p = 0.002) and change in amplitude (p = 0.0005) in circulation (Fig. 2 Extended Data 2A). Amongst the myeloid compartments, spleen recorded significant changes in diurnal oscillations and net abundance in CD group (Fig. 3 B, E). Spleen plays a critical role by acting as a significant reservoir for storage and rapid deployment to sites of inflammation. Our data shows a significant accumulation of Ly6C + monocytes (p < 0.05) in control spleen during the day/inactive phase (ZT0-ZT12 and peak at ZT6) followed by a significant decrement/release in the night/active phase (ZT18) (p < 0.05) which is in agreement with published literature. However, CD Ly6C + monocytes were reported to migrate more in spleen with peak accumulation at two different time points (ZT6 and ZT18) in contrast to a single peak (ZT6) in control (Fig. 3 B, E). Phenotypic shifts in circulating monocytes due to Chronodisruption We had investigated the abundance of each of Monocyte subsets that are involved in inflammation to understand whether CD promote a specific phenotypic differentiation. The gating strategy for the same has been given in (Fig. 1 Extended Data 1A). The diurnal abundance of CD11b + Ly6C + CD86 + monocytes and CD11b + Ly6C + CD163 + monocytes was studied using flow cytometry wherein; significant CD86 + /CD163 + abundance was recorded in CD group (Fig. 3 F-H). The CD86 + numbers peak at ZT12 and were consistently higher in control group whereas; the CD163 + levels peaked at ZT18 indicative of a homeostatic rhythm (Fig. 3 F-H). CD group showed a relative decrement in CD86 + monocytes and a significant increase in CD163 + monocytes (p = 0.0001) at ZT18. These findings suggest that Chronodisruption is associated with a shift toward a CD163⁺-enriched monocyte phenotype in circulation, consistent with an activated immune profile.( 20 , 21 ) Regulatory role of Bmal1 in Clock-chemokine interactions in monocytes Monocyte trafficking and migration is attributed to the diurnal interactions in chemokine receptors and its ligands. CD was able to significantly alter the diurnal oscillation of Ly6C + monocytes and therefore the intracellular oscillations in clock-chemokine expression was studied to understand the basis of altered monocyte trafficking. To validate the Chronodisruption due to CD protocol via BMAL1 and CLOCK protein oscillations in liver (Fig. 3 Extended Data 3A). Untouched monocytes were isolated from blood, spleen and bone marrow at 6h intervals for a 24h period using negative selection based magnetic separation kits. Cosinor analysis records a consistent shift in oscillations, peak time and amplitude due to CD treatment. (Fig. 4 Extended Data 4A). Circulating monocytes recorded upregulation of BMAL1 and CLOCK proteins (p = 0.0001) at ZT18 in CD group that was inverse to the control group. The chemokines CXCR4 (p,0.05) and CCR2 (p < 0.001) also recorded a concomitant increase at ZT18 in CD group with no significant peak recorded in the control group (Fig. 4 A, C). These results indicate an association between altered clock-chemokine oscillations and changes in circulating monocyte activation. Cosinor analysis also showed a similar pattern and confirmed cyclicity in the protein oscillations (Fig. 4 Extended Data 4B). Further, we checked the clock-chemokine oscillations in spleen. The CD group recorded significantly higher levels of BMAL1, CLOCK, CXCR4 and CCR2 at ZT18 and ZT24 (Fig. 4 B, D). Observations imply to the regulatory role of photoperiodic shifts. CCR2 showed a significant increase in CD monocytes. Single peak observed in CCR2 oscillations corroborated with increased monocyte counts reported at ZT18 (Fig. 4 B, D). Circadian oscillation of survival, proliferation and chemotaxis genes are altered by CD Chemokine receptors expressed on the surface of monocytes are activated by its respective ligands secreted by various tissues in the circulation. Receptor-ligand binding leading to the phosphorylation of CXCR4 leading to activation of downstream signaling cascade wherein; the chemotaxis pathway is an integral part of the signaling cascade. We had investigated the effects of CD on chemotaxis pathway that play a role in monocyte diapedesis/extravasation. The PI3K-Akt pathway in monocytes is crucial for survival, growth and inflammatory responses whereas; CDC42 and RAC1 regulate actin polymerization and morphological changes that perquisite before extravasation. We checked the expression of PI3K, AKT, CDC42 and RAC1 in circulating monocytes at every 6h, for 24h (from ZT0-ZT18). CD monocytes exhibited a ~ 4-fold increase in PI3K expression compared with controls (p < 0.0001; mean ± SD). Interestingly, AKT-1 expression was significantly reduced at ZT6, ZT18, and ZT24 relative to control levels (p < 0.0001; normalized to β-actin) (Fig. 5 A, B). Monocytes adapt an amoeboid shape to pass through the endothelial cells into the extracellular matrix and CDC42 and RAC1 mediated F-actin to G-actin polymerization is imperative for migration. In control monocytes, CDC42 was upregulated from ZT12 to ZT24 indicating increased migration of monocytes (Fig. 5 A, B). Finally, mechanistic association to our findings were recorded by Bmal1 knockdown experiment, we transfected THP-1 monocyte derived macrophages with siBmal1 siRNA and collected RNA samples every 6h for a 24h period (Fig. 5 D). Timepoint based oscillations of candidate genes of Clock-Chemokine and Chemotaxis pathways revealed that siBmal1 administration causes downregulation of Cxcr4 and Ccr2 (p < 0.0001). Further, the downstream signaling pathway comprising of Pi3k, Akt1, mTor, Rac1 and Cdc42 (p < 0.001) were significantly downregulated (Fig. 5 C). Lowered Bmal1 expression results in downregulation of chemokine receptor in monocyte derived macrophages To establish a functional relevance of Bmal1 in regulating chemokine expression, we wanted to explore the effects Bmal1 knockdown on THP-1 monocyte derived macrophages. THP-1 human monocytes were differentiated into macrophates using phorbol-12-myristate-13-acetate (PMA 50µM) and were transfected with small interfering RNA (siRNA) for Bmal1(siBmal1). The one without a functional binding site for human genome served as a negative control (siNC) (Fig. 2 D). BMAL1 knockdown at two siRNA concentrations (15 nM and 25 nM) reduced CXCR4 expression by ~ 50% and CCR2 by ~ 60% relative to control cells (p < 0.01). as evidenced by the immunoblots (Fig. 2 A, B). Further, we report that similar reduction was also observed in mRNA transcripts of Bmal1, Cxcr4 and Ccr2 genes (Fig. 2 C), thus validating the role of Bmal1 in regulating chemokine receptor expression. Bmal1 is a known transcription factor regulating rhythmic expression of genes by binding to the E-box enhancer elements in the promoter regions. Integration of publicly available ChIP-seq dataset demonstrates BMAL1 occupancy at regulatory regions of CXCR4 and CCR2 , supporting a transcriptional regulatory relationship that is further functionally validated by BMAL1 knockdown. To determine the association between BMAL1 and CXCR4, we used ChIP-Atlas database to integrate previously published ChIP-seq experiments and, to test the occupancy of BMAL1 in Cxcr4 & Ccr2 gene. Integrative genomic viewer plots revealed a significant binding of Bmal1 at an enhancer region (5’ CATGTG 3’) 17kbp away from transcription start site (TSS) of Cxcr4 gene (Fig. 1 F, G) suggesting that Bmal1 binds to the Cxcr4 promotor. Circadian control of monocyte homing via upregulation of CCR2-CCL2 axis. Monocytes trafficking is a multifactorial process because of its regulation via intra-cellular (Clock-chemokine-chemotaxis pathways) and extra-cellular signals (melatonin, corticosterone and chemokines). Untouched monocytes isolated using negative magnetic separation were stained with CFSE-FITC dye to achieve long term multi-generational staining (Fig. 6 A). CFSE-FITC stained untouched monocytes from control (Non-Manipulated) and CD (Manipulated) groups were adoptively transferred into control or CD mice and allowed to migrate for 24h. At the end of incubation period, percentage of adoptively transferred monocytes in blood, bone marrow, spleen and liver were quantified using flow cytometry (Fig. 6 B). The gating strategy for the same has been given in (Fig. 4 Extended Data 1E). Our data showed, no significant change in abundance of adoptively transferred monocytes in various tissues between C + N, C + M and CD + M groups. Blood and bone marrow recorded a non-significant increment in FITC+ monocytes in CD + M group whereas, spleen and liver recorded higher abundance in C + N group (Fig. 5 Extended Data 1B). Trafficking of manipulated (M) and non-manipulated (N) monocytes under experimentally induced inflammatory conditions (carbon tetrachloride; CCL4 induced chemical hepatotoxicity) was studied in mice (n = 6 per group). Effects of low and high doses (1ml/kg B.W. & 3ml/kg B.W. I.P.) were observed till 72 hours wherein; no mortality was recorded. Both the doses showed significantly high titers of AST and ALT in serum and liver damage at the end of 48h (Fig. 4 Extended Data 1A-D). After 24h of intraperitoneal injection of CCL4, mice were intravenously administered with CFSE-FITC tagged CD (C + M and CCL4 + M) and control monocytes (C + N and CCL4 + N). FITC+ monocytes from blood, spleen, bone marrow and liver were analyzed using flow cytometry (Fig. 6 B). Gating strategy for detection of adoptively transferred monocytes is included in the extended data (Fig. 4 Extended Data 1E). Histopathological analysis revealed significant infiltration of monocytes in liver of CCL4 + N and CCL4 + M groups compared to control group (Fig. 4 Extended Data 1C, D). CCL4 treated groups showed significant ballooning, inflammatory damage and immune cell accumulation as compared to control groups. Both the groups also recorded elevated titers of AST and ALT (p = 0.0001) (Fig. 4 Extended Data 1C, D). Blood did not record any significant changes in FITC+ monocytes from all the groups. However, the highest abundance of adoptively transferred monocytes was recorded in blood as compared to other compartments (Fig. 6 C). We observed significantly higher percentage of adoptive monocytes migrating to bone marrow in CCL4 + M (p = 0.01) group as compared to CCL4 + N (Fig. 6 C). Higher number of monocytes migrating towards the bone marrow can be attributed to significantly higher expression of CXCR4 receptors observed in our study. Further, spleen being the essential site of deployment of monocytes under inflammatory condition, we observed that CD monocytes (C + M) showed significant migration into spleen (Fig. 6 C). This also underlines the fact that under normal conditions monocytes move to spleen. Control monocytes (CCL4 + N; p = 0.0001) migrate more towards spleen as compared to CD (CCL4 + M; p = 0.0001) whose abundance could be tracked in liver. 3 fold higher number of monocytes (p = 0.0001) migrated into the inflamed liver as compared to its control. However, no change was observed for adoptively transferred control monocytes (Fig. 6 C). These results highlight the fact that, under homeostatic conditions both the monocytes recorded identical migratory pattern. Experimentally induced inflammation causes desensitization of CXCR4 accounting for a higher number of monocytes migrating into the inflamed liver. Such a boost in migratory behavior of CD monocytes can be attributed to higher expression of CCR2 chemokine receptor due to an upregulation of Bmal1 protein (Fig. 4 A-D). Our study provides evidence supporting a role for circadian desynchrony-mediated upregulation of Bmal1 in monocytes that eventually culminates in augmented homing towards an inflamed target. Discussion Our findings consolidate a model wherein; the core circadian regulator Bmal1 acts as a transcriptional regulator in monocytes, directly regulating Cxcr4 and Ccr2 to enforce a rhythmic diurnal constraint on chemotaxis—a checkpoint that is imperative during inflammatory challenge. Shift-work cohorts have been reported to exhibit significant, chronic elevations in total monocyte and lymphocyte counts ( 21 , 22 ). We had observed a profound elevation in morning and evening monocyte, WBC, and lymphocyte counts, characterized by upregulated monocytic clock gene and chemokine expression. The core clock gene Bmal1 broadly synchronizes immune responses with circadian environmental signals ( 23 ). Elevated Bmal1 levels can occur through promoter methylation and via coordinated breakdown of its negative regulators PER/CRY ( 24 ). Further, monocytes are highly sensitive to photoperiodic perturbations and respond to chronic sleep deprivation with heightened Bmal1 expression.( 3 , 5 ) In our study, elevated Bmal1 levels in monocytes of sleep deprived individuals can be attributed to the said mechanism but the role of Bmal1 in the regulation of chemokine receptors is not known. We hypothesize that sleep disruption is associated with altered circadian gene expression in circulating monocytes that can possibly disrupt chemokine oscillations and impact their homing. In experimental mice models, myeloid-specific Bmal1 deletion has yielded complex phenotypes, including altered monocyte recruitment in atherosclerosis, regulation of NLRP3 inflammasome activation, enhanced NF-κB–mediated inflammatory responses, and modulation of ferroptosis and phagocytosis.( 25 , 26 ). These reports support a context-dependent, dual role for Bmal1 in macrophage biology. However, studies relying on complete genetic ablation require cautious interpretation, as they may not fully capture the subtle circadian perturbations observed in human pathophysiology, such as chronic sleep deprivation and shift work. Accordingly, the chronodisruption (CD) model employed in our study more faithfully recapitulates the gradual and sustained CD experienced by shift workers, providing a physiologically relevant framework to examine immune consequences. We found that CD altered the diurnal oscillation of inflammatory monocytes (Ly6C⁺) in circulation complemented by coordinated changes in clock genes and chemokine receptors. This was further exemplified into a disrupted circadian rhythm in monocytes that affected their homeostatic release from the bone marrow and caused retention in spleen. These findings are in sync with other research groups that report CD mediated rhythmic activation of chemokine signalling, inflammatory pathways such as NF-κB, and cellular egress from hematopoietic reservoirs( 20 , 27 ). To establish regulatory role of Bmal1 in chemokine expression, our study of Bmal1 KD in THP-1 monocyte-derived macrophages had resulted in significantly lowered Cxcr4 and Ccr2. Further, the in silico chip analysis had identified a sequence upstream of Cxcr4 & Ccr2 promoter that had an affinity for binding to the Bmal1–Clock heterodimer. Both these findings provide compelling evidence on role of Bmal1 in regulating chemokine expression in monocytes. The regulation of chemokines represents a critical integration point for diverse signals ( 5 ) and our work establishes Bmal1 as a important paradigm for Cxcr4 and Ccr2 expression. To establish evidence in support our hypothesis, normal (N) and CD-manipulated (M) monocytes were adoptively transferred in mice with healthy or an inflamed liver (carbon tetrachloride; CCL4 treated). Though, there were no significant changes observed in homing scores of N and M monocytes in healthy mice, a 3 fold increase was recorded in the latter. This amounts to a critical divergence in tropism of M monocytes in response to an inflammatory challenge that can be attributed to an upregulated Bmal1-chemokine axis. In a study involving developmental BMAL1 KO, the circadian monocyte trafficking was found to cause CCL2 upregulation (Nguyen et al., 2013). The said observation was implicated as the cause for augmented monocyte trafficking. It may be noted that, the monocyte-autonomous CCL2 secretion model may be context-dependent and may reflect an artificial scenario wherein developmental knockout of BMAL1 unmasks CCL2 expression. This scenario differs from the physiological chronodisruption reported in our study involving Cxcr4 and Ccr2 upregulation mediated increased monocyte trafficking. Our data suggests that prior interpretations of BMAL1’s role in immunity may require re-evaluation in context of shift work, jet lag, or metabolic diseases. In summary, this study establishes that the circadian regulator BMAL1 acts as a key regulator of monocyte chemokine receptors viz. CXCR4 and CCR2, to enforce rhythmic control over their chemotaxis. Chronic sleep deprivation disrupts this checkpoint, elevating Bmal1 that drives pathological chemokine receptor expression. Consequently, monocytes exhibit aberrant tissue trafficking and splenic retention, under chronodisruptive conditions. This Bmal1-driven reprogramming, augments monocytes toward inflamed tissues upon a challenge thus positioning the monocyte-Bmal1-chemokine axis as a critical effector of Chronodisruption. Limitations (i) While we integrate human observations with mouse and cellular models to provide translational insight, the human component is constrained by sample size (n = 20) and reliance on self-reported sleep measures. Use of actigraphy and larger cohorts would strengthen the human findings. (ii) Adoptive transfer shows altered homing to inflamed liver, the relevance of this reprogramming to specific chronic inflammatory diseases (e.g., atherosclerosis or metabolic syndrome) requires testing in dedicated disease models. Despite these limitations, our multi-system approach establishes that circadian disruption elevates BMAL1 in monocytes, driving chemokine receptor expression and biasing monocytes toward inflamed tissues—a phenotype absent in homeostasis—thus identifying the monocyte-BMAL1-chemokine axis as a potential target in sleep-disruption-associated inflammation. Methods Human Monocyte study Healthy male and female volunteers without any known comorbidities were recruited for the study. All participants completed a detailed questionnaire (Supplementary Table 3) assessing their weekly sleep patterns. Based on questionnaire responses, volunteers were categorized into two groups: control (C) and sleep-disrupted/chronodisrupted (CD). A total of 20 participants (male:female ratio 12:8; age range 21–40 years) were enrolled according to predefined inclusion and exclusion criteria (Supplementary Table 3). None of the participants had a known history of chronic or long-term medical disorders. Written informed consent was obtained from all participants prior to sample collection. Peripheral blood samples were collected by a trained laboratory technician under the supervision of a certified pathologist as per the standard clinical procedures at BlueCross Pathology Laboratory, Makarpura, Vadodara (IMA No. 1093). Blood collection was performed at two time points: morning (09:00–11:00 h) and evening (19:00–21:00 h), with a one-week interval between consecutive sampling sessions. From each collection, 500 µL of blood was used for complete blood count and total lipid profile analysis. Untouched monocytes were subsequently isolated from the remaining sample using the Dynabeads™ Untouched Human Monocyte Isolation Kit (Invitrogen, Thermo Fisher Scientific, USA), according to the manufacturer’s instructions. Cell line and culture Monocytic Leukemia cell line THP-1 was a kind gift from Dr. Arunika Mukhopadhaya, IISER, Mohali. THP-1 cells were maintained in complete Rosewell Park Memorial Institute- 1640 medium (Gibco) supplemental with 1x Antibiotic-Antimycotic Cocktail (Himedia Laboratories, Mumbai, India), 10% fetal bovine serum (Value FBS, Thermo Fisher Scientific). Cells were regularly tested for mycoplasma, and all the experiments were performed between passage number 12 and 19. A new aliquot of the cell line was thawed and cultured consecutively for < 2 months. THP-1 monocytes were differentiated into Human monocyte derived macrophages as described previously ( 28 ) and 50% Horse serum (Horse Serum, Thermo Fisher Scientific) was used to resynchronize the clock before setting up of each biological replicate. siRNA based Bmal1 Knockdown THP-1 monocytes were differentiated into monocyte derived macrophages seeded onto a 24 well plate at concentration of 1 x 105 cell/well and were incubated in complete RPMI-1640 medium (Gibco, Thermo Fisher Scientific) for 24 hours. Later cells were transfected with two different concentrations of siRNA for Bmal1 (si-Bmal1) and negative control (si-NC) (Qiagen Germany) having no sequential binding sites in human genome using Lipofectamine 3000 (Thermo fisher Scientific, USA) transfection reagent. siRNA and transfection reagents were diluted in a low protein, serum reduced cell culture medium Opti-MEM (Thermo fisher Scientific, USA), incubated for 20 mins for the formation of RNA-reagent complex and slowly layer on to differentiated monocyte derived macrophages. Incomplete media was added to make up the volume of the complete system up to 250ul and incubated for 24 hours under 5% CO2. RT-PCR Total RNA was purified TRizol reagent (Thermo fisher scientific,USA) following manufacturers protocol. Isolated RNA was quantified using Take3 microvolume plate (Agilient Biosciences) used with Synergy HTX microplate reader. 1000ng of total RNA was reverse transcribed using BIORAD cDNA synthesis Kit (Biorad, USA). cDNA samples were then subjected to quantitative real-time PCR analysis using Hi-SYBR Master mix (Himedia Laboratories, India) following manufacturer’s instructions on a Qunatstudio 5 Real time PCR (Invitrogen). 18s rRNA was used a housekeeping gene for normalization of the samples. Primers specific for each gene were synthesized by Eurofins, India and specific sequences are available in Supplementary Table 2.( 6 ) Western Blotting Collected cells and tissues were lysed in 1X RIPA buffer on ice for 30 min, with protease and phosphatase inhibitors tablets (Roche, Sigma). Lysates were centrifuged at 12,000g for 5 min at 4°C to obtain the supernatant. Protein content was then quantified by bicinchoninic acid assay (Biorad, USA) and diluted to a final concentration of 1–2 µg µl–1. After the addition of 5× SDS–PAGE loading buffer (Himedia Laboratories, India), samples were boiled at 95°C for 10 min, resolved via SDS–PAGE and transferred to a PVDF membrane (Biorad, USA). Membranes were blocked in Pierce Protein Free Block Buffer (Thero Fisher Scientific, USA) at room temperature for 1 h and subsequently incubated with the primary and secondary antibodies. Antibodies Bmal1 (1:1000), Clock (1:000) and anti-rabbit-HRP conjugated (1:2000) were purchased from Invitrogen, Thermo fisher, USA. The antibodies Pi3k (1:1000), Akt-1 (1:1000), cDC42 (1:1000), Cxcr4 (1:1000), Ccr2/Cd-192 (1:1000) and Actin (1:1500) were purchased from Elabsciences Bionovation Inc. Blot signals were detected using a Chemidoc Touch (Biorad, USA) or were developed on X-ray films in a dark room. Human Monocyte Isolation Peripheral blood mononuclear cells (PBMC) were prepared by centrifugation on a Hisep LSM 1077 (LS001; HiMedia Laboratory Pvt. Limited, India). Untouched monocytes were isolated using Invitrogen Dynabeads Untouched Human Monocyte Isolation Kit (Thermo fisher Scientific, USA) according to manufacturer’s protocol. Isolated monocytes were subjected to downstream gene expression analysis. Animals C57BL/6J WT mice (10–12 weeks old) were procured from Advanced center for treatment research and education in cancer, Mumbai, India. 87 male mice were housed and routinely handled in Animal House facility, Department of Zoology, Faculty of Science, The Maharaja Sayajirao University of Baroda, Vadodara, Gujarat, India as per CCSEA guidelines. All mice were fed with standard mice chow. Animal protocols were reviewed and approved (MSU-Z/IAEC08/01-2024) by the Institutional Animal Ethical Committee (IAEC), Department of Zoology, Faculty of Science, The Maharaja Sayajirao University of Baroda, Vadodara, Gujarat, India. All the protocols were performed as per ARRIVE guidelines and mice were euthanized; samples were collected as per IAEC and CCSEA guidelines. Animal Experiments After two weeks of acclimatization, 10–12 weeks old mice were randomly divided into two groups (N = 25; n = 5/timepoint). Group I: Control mice fed with standard chow diet and maintained in LD 12:12; Group II: Chronodisruption (CD) mice fed on standard chow diet and subjected to phase advance-phase delay photoperiod as described previously (Ref). Mice were fasted for 8–10 hours and blood, spleen, bone marrow and liver were harvested at different timepoints (ZT0, 6, 12, 18 & 24). The samples were divided into 4 parts and stored for flow cytometry, in RNA Latter (Thermo fisher scientific, USA), in 4% PFA (for histopathology) or in -80° C (for immunoblots). Single cell suspension of spleen and liver was prepared by passing through 40-micron cell strainer (Geneaxy, India) followed by fixation with 4% paraformaldehyde. Sample were analyzed using BD FACS ARIA II. The second in vivo experiment was performed to standardize the operational dose of CCL4, wherein mice were acclimatized for two weeks and later, randomly divided into 4 groups (n = 3/group). Group I: Control (0.9% ns), Group II: Vehicle control (Olive Oil; Sigma Aldrich), Group III: CCL4 Low dose (1ml/kg; 1:4 dilution in olive oil) Group IV: CCL4 High dose (5ml/kg; 1:4 dilution in olive oil). Group I, II, III, IV received a single intraperitoneal injection of ns, olive oil or CCL4. Cage side observations were recorded for 72 hours to document behavioural perturbations and survival. Later, mice were sacrificed and, blood, liver and spleen were collected at 24-hour and 48-hour time points. The third in vivo study involved monitoring the monocyte homing in C57BL/6J mice. After the phase of acclimatization as mentioned above, the mice were randomly divided into 05 groups viz. Group I: Sham (ns i.v.) Group II: Control recipient + normal monocytes from healthy donor (C + N), Group III: Control recipient + manipulated monocytes from CD donor (C + M), Group IV: CCL4 + normal monocytes (CCL4 + N) and Group V: CCL4 + manipulated monocytes (CCL4 + M). The doses of (ns, olive oil or CCL4) were injected intraperitoneally and cage side observations were recorded for 24 hours. Later, CFSE tagged monocytes (N or M) were injected intravenously (in C or CCL4 treated mice). After 48 hours, mice were anesthetized for collection of blood, bone marrow, spleen and liver. Mouse Monocyte isolation Mononuclear cells were isolated (at various time points as mentioned above) using Hisep LSM 1084 (LS003; HiMedia Laboratory Pvt. Limited, India). Later, the untocuhed monocytes were isolated using a MojoSort Mouse monocyte isolation kit (Biolegend) and were subjected to downstream flow cytometry and gene expression analysis. Flow cytometry analysis A timepoint based flow cytometry analysis was carried to understand monocyte migration in bone marrow, blood and spleen following photoperiod induced chronodisruption. Blood, bone marrow and spleen were collected as mentioned above and a single cell suspension from blood, and bone marrow was subjected to Ammonium-chloride-potassium (ACK) lysis buffer for 10 mins. The cell pellet was washed with PBS twice and resuspended in PBS. Single-cell suspension from spleen was prepared by mechanically disrupting the tissue using a syringe plunger through a 40-micron cell strainer and ACK lysis was carried out by same process. Fc receptor from single cell suspension from blood, bone marrow and spleen were blocked using Anti-mouse CD16/32 Antibody (2.4G2) (Elabsciences, USA). Cell suspension was stained for 30 mins at 4°C with E-lab Fluor Violet 540 Anti-mouse Ly6C (E-AB-F1121T3), PE/Cyanine 7 Anti-mouse CD11b (E-AB-F1081H), FITC Anti-mouse CD86 (E-AB-F0994C) and APC Anti-mouse CD163 (E-AB-F1295C); subsequently washed with cell staining buffer (E-CK-A107) and fixed with 4% PFA (for 5mins). Excess PFA was removed by PBS wash and resuspension in cell staining buffer. A single timepoint (ZT12) collection of blood, bone marrow, spleen and liver was done for monocyte homing studies. Single cell suspension of blood, bone marrow and spleen were prepared as described above. Liver (approx 50 µg) was cut and incubated in collagenase type IV for 15 mins at 37°C. A single cell suspension was prepared by mechanically disrupting the tissue using a syringe plunger and passed through 40-micron cell strainer. ACK lysis protocol was done as mentioned above. The samples were analyzed using BD FACS Aria II and FlowJo was used for downstream analysis. CFDA, SE staining and Monocyte adoptive transfer Donor mice: Control or chronodisrupted groups served as the donor mice. Monocytes were collected from the control (N; Normal monocytes) or chronodisrupted mice (M; Manipulated monocytes) as described previously using MojoSort Mouse monocyte isolation kit. CFDA, SE dye was selected due to their superior performance in terms of bright and uniform staining of all cells, longer retention time and minimal toxicity. Untouched monocytes were stained, washed twice with PBS and a cell count of 3 x 106 cells/100µL was used for further study. Recipient mice: Control (olive oil i.p.) or CCL4 (injected with 1ml/kg CCL4 in 1:4 dilution in olive oil, i.p.) were used for this study. These mice received an adoptive transfer of monocytes (received from donor mice: normal (N) or manipulated (M) (100µL/ mice) through tail vein injection following lamp-based vasodilation. Post 24 hour of adoptive transfer, mice were euthanised and monocyte homing was studied in blood, bone marrow, spleen and liver using flow cytometry. Liver function test Circulating liver enzymes (AST, ALT, and ALP) and serum lipid profile parameters, including total lipids, total cholesterol, triglycerides, LDL, VLDL, HDL, cholesterol/HDL, and LDL/HDL ratios, were assessed using standard commercial diagnostic kits (Reckon Diagnostics, Vadodara, Gujarat, India).( 29 ) Liver Histopathology Liver samples (n = 6/group) were autopsied, washed in PBS and fixed in 4% paraformaldehyde. Paraffin-embedded, liver sections (5 µm) were stained with haematoxylin and eosin (H&E) and photographed on Leica DM 2500 microscope. Qualitative evaluation focused on inflammatory foci, immune cell infiltration, sinusoidal alterations and disruption of hepatic cord organization were observed.( 29 ) Statistical analysis All the data were analyzed in Prism 10 (GraphPad). Statistical test such as ANNOVA, student t-test were performed as indicated in the figure legends, and number of replicates are also provided. All error bars represent mean ± S.D. Mice were randomly assigned to the treatment groups and number mice per group are as indicated. Data was presumed to be normally distributed. Statistical significance was defined as *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001 vs Control, the individual Declarations Data Availability Data from this study is available upon request. Source Data is provided with this paper. Contributions R.K., A.V., H.V. and R.V.D. conceived the project, designed the experiments, analyzed and interpreted the data. R.K., H.S., and R.V.D. wrote the paper. R. K., H.S., M.K., P.P., S.K., performed the human volunteer study. R.K. and H.S. performed all the in vitro experiments. R.K., H.S., M.K., P.P., S.K. and S.J. performed the mouse experiments. R.K. initiated and performed the flow cytometry study, carried out the data analysis of monocyte trafficking and monocyte adoptive transfer studies. R.V.D. directed the study, interpreted the data and supervised the work. Corresponding author Correspondence to Ranjitsinh V. Devkar Ethics Declaration Competing Interests The authors declare no competing interests. Acknowledgements We acknowledge the funding provided by the Department of Biotechnology, Ministry of Science & Technology, Government of India (BT/PR42042/MED/30/2323/2021 to R.V.D.). R.K. and H.V. were supported by LTMT Senior Research Fellowship, Lady Tata Memorial Trust Senior Research Fellowship. H.S. was supported by DBT BET Fellowship, Department of Biotechnology, Ministry of Science & Technology, Government of India. A.V. was supported by DST Purse Fellowship, Department of Science & Technology, Ministry of Science & Technology, Government of India. We also acknowledge the contribution by Mr. Bhaumik Jaiswal for the help rendenred during the study. We thank the technical staff of Flow Cytometry Shared Lab Facility, Gujarat Biotechnology Research Center, Gandhinagar, Gujarat, India for their excellent technical assistance. References Fagiani F, Di Marino D, Romagnoli A, Travelli C, Voltan D, Mannelli LDC, et al. Molecular regulations of circadian rhythm and implications for physiology and diseases. Signal Transduction and Targeted Therapy 2022 7:1 [Internet]. 2022 Feb 8 [cited 2026 Jan 27];7(1):41-. Available from: https://www.nature.com/articles/s41392-022-00899-y Nguyen KD, Fentress SJ, Qiu Y, Yun K, Cox JS, Chawla A. Circadian gene Bmal1 regulates diurnal oscillations of Ly6C(hi) inflammatory monocytes. Science [Internet]. 2013 [cited 2026 Jan 27];341(6153):1483–8. 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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-8894070","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":592225951,"identity":"5a5a17f7-9216-414f-be05-ade7df2a8716","order_by":0,"name":"Ranjitsinh Devkar","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0002-9863-7418","institution":"The Maharaja Sayajirao University of Baroda","correspondingAuthor":true,"prefix":"","firstName":"Ranjitsinh","middleName":"","lastName":"Devkar","suffix":""},{"id":592225952,"identity":"7a1e617a-162f-4d92-aa17-c4575f7465f3","order_by":1,"name":"Rhydham Karnik","email":"","orcid":"","institution":"The Maharaja Sayajirao University of Baroda","correspondingAuthor":false,"prefix":"","firstName":"Rhydham","middleName":"","lastName":"Karnik","suffix":""},{"id":592225953,"identity":"f6abb293-c025-4b61-85e3-a0973ffde35e","order_by":2,"name":"Helly Shah","email":"","orcid":"","institution":"The Maharaja Sayajirao University of Baroda","correspondingAuthor":false,"prefix":"","firstName":"Helly","middleName":"","lastName":"Shah","suffix":""},{"id":592225954,"identity":"a4d2007c-8b2d-46e7-8820-7ee389a44bb8","order_by":3,"name":"Aliasgar Vohra","email":"","orcid":"","institution":"The Maharaja Sayajirao University of Baroda","correspondingAuthor":false,"prefix":"","firstName":"Aliasgar","middleName":"","lastName":"Vohra","suffix":""},{"id":592225955,"identity":"e57eb673-0ffc-4136-bcc8-6253ecc1761f","order_by":4,"name":"Hitarthi Vyas","email":"","orcid":"","institution":"The Maharaja Sayajirao University of Baroda","correspondingAuthor":false,"prefix":"","firstName":"Hitarthi","middleName":"","lastName":"Vyas","suffix":""},{"id":592225956,"identity":"1c97b91f-9bdb-4336-b448-4aad04d9bda4","order_by":5,"name":"Mahamadtezib Khatri","email":"","orcid":"","institution":"The Maharaja Sayajirao University of Baroda","correspondingAuthor":false,"prefix":"","firstName":"Mahamadtezib","middleName":"","lastName":"Khatri","suffix":""},{"id":592225957,"identity":"8308592f-c2d2-401b-b4db-da490b6f49fa","order_by":6,"name":"Smit Kanojiya","email":"","orcid":"","institution":"The Maharaja Sayajirao University of Baroda","correspondingAuthor":false,"prefix":"","firstName":"Smit","middleName":"","lastName":"Kanojiya","suffix":""},{"id":592225958,"identity":"4c95ec3e-1d4a-4155-91b6-efb9a57295b4","order_by":7,"name":"Purva Parmar","email":"","orcid":"","institution":"The Maharaja Sayajirao University of Baroda","correspondingAuthor":false,"prefix":"","firstName":"Purva","middleName":"","lastName":"Parmar","suffix":""}],"badges":[],"createdAt":"2026-02-16 14:42:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8894070/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8894070/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102963795,"identity":"c7007bc6-d14b-437e-8fc7-e00eccf4ebb4","added_by":"auto","created_at":"2026-02-19 04:20:34","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2611850,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA,\u003c/strong\u003e Experimental schema, questionnaire-based survey was followed by blood collection at two different timepoints (morning and evening), monocyte isolation and western blot analysis. \u003cstrong\u003eB\u003c/strong\u003e, Complete blood count of healthy vs sleep disrupted individuals showing total number of WBC, lymphocytes, polymorphs and monocytes. \u003cstrong\u003eC\u003c/strong\u003e, Differential monocyte counts from morning to evening to \u003cstrong\u003eD,E\u003c/strong\u003e, immunoblots of evening monocytes isolated from blood (\u003cem\u003eControl and CD\u003c/em\u003e). Actin was run on same gel, loaded with the same lysate aliquots. Quantification of Clock-chemokine proteins levels (n=10) in monocytes with quantified graphs \u003cstrong\u003e(D)\u003c/strong\u003e and representative blot images \u003cstrong\u003e(E)\u003c/strong\u003e. Unpaired student t-test for comparing mean to control group \u003cstrong\u003e(A-D)\u003c/strong\u003e. Bar and error indicate mean ± S.D. of the fold change as compared to control. P-values are depicted as *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001 vs Control.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8894070/v1/6ba568b7ff8643bd4d0830d7.png"},{"id":102890214,"identity":"2eaa7408-4adc-4070-ba24-ae2286d4613c","added_by":"auto","created_at":"2026-02-18 04:31:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":6079224,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e, Experimental schema, Top, C57BL/6J mice were subjected to photoperiod manipulation induced chronodisruption for a total period of 16 weeks. At the end protocol, blood, spleen and bone marrow were isolated for flow cytometry analysis followed by monocyte isolation for gene expression analysis. \u003cstrong\u003eB\u003c/strong\u003e, Flow cytometry plots of blood, bone marrow and spleen monocytes collected every 6 hours for 24 hours. \u003cstrong\u003eC-E\u003c/strong\u003e, timepoint based quantified graphs of CD11b+ (n=3), CD11b+Ly6c+(n=3), CD11b+Ly6C-(n=3) cell percentage in blood, bone marrow and spleen at ZT 0-24. Data were analyzed by two-way ANOVA with Geisser-Greenhouse correction followed by Šídák's multiple comparisons test. Dot and error indicate mean ± S.D. as compared to control. P-values are depicted as *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001 vs Control.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8894070/v1/a550b0cde3b92839d37725fd.png"},{"id":102963316,"identity":"0f0cd7c3-f45a-4eac-9a39-d0b23e89030e","added_by":"auto","created_at":"2026-02-19 04:15:24","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":5533768,"visible":true,"origin":"","legend":"\u003cp\u003eImmunoblots of monocytes isolated at 5 different timepoint ZT0-24 from blood or spleen of mice (\u003cem\u003eControl and CD\u003c/em\u003e). Actin was run on same gel, loaded with the same lysate aliquots. \u003cstrong\u003eA-C\u003c/strong\u003e, Flow cytometry plots of Ly6C+CD163+(n=3) and Ly6C+CD86+(n=3) cells in blood at various timepoints. \u003cstrong\u003eB, C\u003c/strong\u003e, Quantified graphs of cell percentage at various timepoints in bone marrow and spleen. \u003cstrong\u003eD\u003c/strong\u003e, \u003cstrong\u003eE\u003c/strong\u003e, Quantification of clock-chemokine protein levels (n=3) from blood using mouse monocyte isolation kits with representative blots \u003cstrong\u003e(D)\u003c/strong\u003e and quantified graphs \u003cstrong\u003e(E)\u003c/strong\u003e. \u003cstrong\u003eF, G\u003c/strong\u003e, Quantification of clock-chemokine protein levels (n=3) from spleen using mouse monocyte isolation kits with representative blots \u003cstrong\u003e(F)\u003c/strong\u003e and quantified graphs \u003cstrong\u003e(G)\u003c/strong\u003e. Data were analyzed by two-way ANOVA with Geisser-Greenhouse correction followed by Šídák's multiple comparisons test. Dot and error indicate mean ± S.D. of the fold change as compared to control. P-values are depicted as *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001 vs Control.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8894070/v1/38daebe734ed66e26463a8ad.png"},{"id":102963637,"identity":"f2fc1e4f-296f-41cf-949c-cf6ed64410ab","added_by":"auto","created_at":"2026-02-19 04:19:40","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":6450490,"visible":true,"origin":"","legend":"\u003cp\u003eImmunoblots of monocytes isolated at 5 different timepoint ZT0-24 from blood or spleen of mice (\u003cem\u003eControl and CD\u003c/em\u003e). Actin was run on same gel, loaded with the same lysate aliquots. \u003cstrong\u003eA, B\u003c/strong\u003e, Quantification of chemotaxis pathway protein levels (n=3) at ZT0-24 in monocytes isolated from blood using mouse monocyte isolation kits with representative blots \u003cstrong\u003e(A)\u003c/strong\u003e and quantified graphs \u003cstrong\u003e(B). C\u003c/strong\u003e, THP-1 monocytes synchronized with serum deprivation and subjected to Bmal1 knockdown. Timepoint based mRNA quantification of Clock-chemokine-chemotaxis genes at ZT24-48. Two-way ANNOVA with Geisser Greenhouse correction. Dot and error indicate mean± S.D. of the fold change as compared to control. P-values are depicted as *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001 vs Control.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-8894070/v1/bda6e72789823a86381678e6.png"},{"id":102890208,"identity":"030e4745-0572-4b03-a5e1-dc45093315aa","added_by":"auto","created_at":"2026-02-18 04:31:34","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":3081159,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e, Immunoblots of THP-1 monocyte differentiated into macrophages upon stimulation by PMA and subjected to Bmal1 knockdown (\u003cem\u003esi-NC, si-BMAL1 at concentration of 15nM and 25nM\u003c/em\u003e). Representative blot images of THP-1 monocyte derived macrophages treated with two varying concentrations of anti-Bmal1 siRNA for 24 hr. \u003cstrong\u003eB\u003c/strong\u003e, Quantified graphs of relative protein expression (n=3) normalized to Actin. \u003cstrong\u003eC\u003c/strong\u003e, Transcriptional quantification of Clock-chemokine genes post-Bmal1 Knockdown. \u003cstrong\u003eD\u003c/strong\u003e, Experimental schema, THP-1 monocytes differentiated into macrophages using PMA (100mM) for 24 hours and subjected to Bmal1 knockdown for 24 hours with si-Bmal1 and si-NC used as negative control. \u003cstrong\u003eE\u003c/strong\u003e, Occupancy of Bmal1 on CXCR4 enhancer region is shown in integrative genomic viewer plots of Thp-1 Chip-seq datasets from Chip-Atlas database. One-way ANOVA with Dunnett's post-hoc test (comparing each dose to control) \u003cstrong\u003e(B, C)\u003c/strong\u003e. Bar and error indicate mean± S.D. of the fold change as compared to control. P-values are depicted as *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001 vs Control.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-8894070/v1/fc991dfb2352020a7947992c.png"},{"id":102890218,"identity":"a73ee15b-54d8-43d2-b698-4c1cefb8bd55","added_by":"auto","created_at":"2026-02-18 04:31:34","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":9900311,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e, Flow cytometry plot of adoptive transferred FITC+ monocytes in blood, bone marrow, spleen and liver in various experimental groups depicting monocyte migration from blood to peripheral tissues. \u003cstrong\u003eB\u003c/strong\u003e, Quantified graphs of adoptively transferred FITC+ monocytes with % population on the left and absolute number on the right in blood, bone marrow, spleen and liver. \u003cstrong\u003eC\u003c/strong\u003e, Experimental schema, C57BL/6J mice are subjected to photoperiod induced chronodisruption and monocytes are isolated from blood and bone marrow are stained with CFSE dye and adoptively transferred to C57BL/6J mice treated with or without CCL4 to induce hepatic inflammation. One-way ANNOVA with Geisser Greenhouse correction. Dots, bar and error indicate mean± S.D. as compared to control. P-values are depicted as *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001 vs Control.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-8894070/v1/f0734df7e651c7b8a4bf43c5.png"},{"id":104404671,"identity":"2213896b-5696-4017-85c1-e937424e5e07","added_by":"auto","created_at":"2026-03-11 12:20:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":33485998,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8894070/v1/a0c8815d-df9c-49be-9d17-9f8620e79a25.pdf"},{"id":102890205,"identity":"b031a746-1ec3-40fd-96a0-8c8f57fc17e7","added_by":"auto","created_at":"2026-02-18 04:31:33","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":17085,"visible":true,"origin":"","legend":"Supplementary Table","description":"","filename":"SuplementaryTable1X2.docx","url":"https://assets-eu.researchsquare.com/files/rs-8894070/v1/7f027b59fbf33cb6ff066505.docx"},{"id":102890206,"identity":"fe60a810-90f8-4e78-a91a-cd4436704fec","added_by":"auto","created_at":"2026-02-18 04:31:33","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1179654,"visible":true,"origin":"","legend":"Supplementary Data 5","description":"","filename":"Fig.5ExtendedData2.tif","url":"https://assets-eu.researchsquare.com/files/rs-8894070/v1/26be6826f10a9b598484c5cb.tif"},{"id":102964128,"identity":"09d9d5c1-5d9f-4087-ac47-0af5145fc3fa","added_by":"auto","created_at":"2026-02-19 04:21:32","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":2201886,"visible":true,"origin":"","legend":"Supplementary Data 2","description":"","filename":"Fig.2ExtendedData2.tif","url":"https://assets-eu.researchsquare.com/files/rs-8894070/v1/cc393a843917919cf2364245.tif"},{"id":102890211,"identity":"cdcccbfd-7c09-41c3-9212-b1807dc57649","added_by":"auto","created_at":"2026-02-18 04:31:34","extension":"tif","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":6646606,"visible":true,"origin":"","legend":"Supplementary Data 3","description":"","filename":"Fig.3ExtendedData.tif","url":"https://assets-eu.researchsquare.com/files/rs-8894070/v1/09683022ce88077ccf669f7c.tif"},{"id":102963959,"identity":"73660936-5412-4d6f-9815-9597b992beac","added_by":"auto","created_at":"2026-02-19 04:20:59","extension":"tif","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":6126398,"visible":true,"origin":"","legend":"Supplementary Data 9","description":"","filename":"Fig.5Sourcedata2.tif","url":"https://assets-eu.researchsquare.com/files/rs-8894070/v1/40830e04ab0bcb6203c96d26.tif"},{"id":102890210,"identity":"3173bf1f-4caf-4014-bdbf-ff5c7484cab4","added_by":"auto","created_at":"2026-02-18 04:31:34","extension":"tif","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":1993990,"visible":true,"origin":"","legend":"Supplementary Data 4","description":"","filename":"Fig.4ExtendedData2.tif","url":"https://assets-eu.researchsquare.com/files/rs-8894070/v1/95c9d445e054b1fbe05c43b4.tif"},{"id":102964238,"identity":"2fe4ab02-7d67-460d-8105-939878ccab2c","added_by":"auto","created_at":"2026-02-19 04:21:51","extension":"pdf","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":1506504,"visible":true,"origin":"","legend":"Supplementary Data 10","description":"","filename":"SupplementaryMaterial3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8894070/v1/cd4e577870abe336c445c682.pdf"},{"id":102963608,"identity":"03563212-36ee-4e05-9333-8c116337b306","added_by":"auto","created_at":"2026-02-19 04:19:21","extension":"tif","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":3058958,"visible":true,"origin":"","legend":"Supplementary Data 6","description":"","filename":"Fig.6ExtendedData1.tif","url":"https://assets-eu.researchsquare.com/files/rs-8894070/v1/5890f48612e195440a944896.tif"},{"id":102890217,"identity":"4c24d1f5-0f0f-4bc2-857a-310cc1056776","added_by":"auto","created_at":"2026-02-18 04:31:34","extension":"tif","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":23816286,"visible":true,"origin":"","legend":"Supplementary Data 1","description":"","filename":"Fig.1ExtendedData.tif","url":"https://assets-eu.researchsquare.com/files/rs-8894070/v1/e2a28f2933db5c54002e08b1.tif"},{"id":102890219,"identity":"fa8b1966-b65b-4463-b18d-c40d2cb81af9","added_by":"auto","created_at":"2026-02-18 04:31:34","extension":"tif","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":26204122,"visible":true,"origin":"","legend":"Supplementary Data 7","description":"","filename":"Fig.7ExtendedData2.tif","url":"https://assets-eu.researchsquare.com/files/rs-8894070/v1/74b8b30df0f7d0afc89a879a.tif"},{"id":102890221,"identity":"486efbbf-3438-445a-80a2-4ce2c70648c8","added_by":"auto","created_at":"2026-02-18 04:31:34","extension":"tif","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":11061582,"visible":true,"origin":"","legend":"Supplementary Data 8","description":"","filename":"Fig.1SourceData1.tif","url":"https://assets-eu.researchsquare.com/files/rs-8894070/v1/f055ce841ca15d617ce2dc8f.tif"}],"financialInterests":"(Not answered)","formattedTitle":"Circadian Clock protein Bmal1 drives inflammatory homing in monocytes via augmented Cxcr4 and Ccr2 axis","fulltext":[{"header":"Main","content":"\u003cp\u003eThe circadian clock is an evolutionarily conserved, cell-autonomous transcriptional-translational feedback loop (TTFL) that orchestrates\u0026thinsp;~\u0026thinsp;24-hour rhythms in physiology and gene expression, synchronizing cellular processes with the light-dark cycle. Core clock proteins, including BMAL1 and CLOCK, drive the rhythmic expression of clock-controlled genes (CCGs), which regulate diverse functions from metabolism to immune responses.(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) In the immune system, a temporal regulation is not merely a passive response, but an active anticipatory program that gates processes such as leukocyte circulation, cytokine release and antimicrobial defence. Disruption of this finely tuned temporal order (chronodisruptiuon; CD) is a pervasive feature of modern life and a significant contributor to chronic disease.(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) It results from environmental insults such as shift work, chronic jet lag and sleep disorders.(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) This disruption is a hallmark and exacerbating factor in a range of conditions including cardiometabolic disorders, autoimmune diseases, and neuroinflammation.(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) Non-Alcoholic Fatty Liver Disease (NAFLD), rheumatoid arthritis or cancer furthers disease progression through ill-defined inflammatory pathways and by triggering a vicious cycle that furthers sleep disturbances and nocturnal wakefulness leading to CD.(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) A cardinal feature of this circadian-immune interface is the regulation of myeloid cell trafficking.(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eMonocytes are the key mediators of innate immunity and tissue homeostasis that exhibit robust diurnal oscillations in their release from the bone marrow and their recruitment to tissues.(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) This homing is governed by the rhythmic expression of chemokine receptors, notably CCR2 and CXCR4, that respond to spatial gradients of their ligands (e.g., CCL2, CXCL12).(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) Under circadian control, this system ensures precise temporal delivery of monocytes and balancing immune surveillance by preventing excessive tissue inflammation. When this temporal gating fails, the consequences are profound. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) Aberrant, non-rhythmic monocyte infiltration into tissues is a key driver of the low-grade, persistent inflammation that characterizes metabolic syndrome and atherosclerosis.(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) In conditions like psoriasis and inflammatory bowel disease, inappropriate leukocyte recruitment directly contributes to lesion formation and flare-ups.(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) The nocturnal influx of inflammatory monocytes into tissues, if mistimed or excessive, can shift a protective immune response toward a pathogenic, tissue-destructive state.(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) Despite this clear link, the precise molecular mechanism by which the core circadian clock directly governs the chemotactic machinery of monocytes\u0026mdash;and how this mechanism breaks down in disease\u0026mdash;remains a critical and unresolved question.\u003c/p\u003e \u003cp\u003ePrevious attempts to define this link have relied heavily on global or myeloid-specific knockout mice models, representing an extreme of circadian dysfunction (complete loss) rather than the dysregulation (altered amplitude or timing) synonymous with the human diseases. This gap has left a fundamental unanswered question on how the pathological upregulation or mistiming of core clock components directly reprogram monocyte homing and promote inflammation. In this study, we address this gap by testing the hypothesis that core clock protein BMAL1 may regulate the transcription of chemokine receptors (CXCR4 and CCR2). Using a translational approach, we integrate the data from sleep-disrupted human cohort, a murine model of shift work and in vitro studies. Taken together, we report on consequences of chronic sleep disruption as a core regulator of rhythmic monocyte trafficking via a novel BMAL1-chemokine receptor axis. This axis accounts for an aberrant tissue homing of monocytes that may have far reaching consequences in metabolic and immune disorders.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSleep deprivation is associated with altered monocyte numbers and core clock gene expression in humans\u003c/h2\u003e \u003cp\u003eWe studied the complete blood count (CBC) of healthy (Control) and Sleep disrupted (CD) individuals segregated as per our circulated questionaries (Supplementary Table\u0026nbsp;1, 3) to assess possible manifestations of altered sleep-wakefulness cycle in circulation. Individuals reporting long-term irregular sleep patterns, including consistent late-night work shifts, habitual sleep onset after 23:00, and weekday-to-weekday sleep timing variability (\u0026gt;\u0026thinsp;2-hour difference on \u0026ge;\u0026thinsp;3 days/week), were classified as the Sleep Disrupted (CD) group.(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNext, we undertook complete blood count at two different timepoints to understand implications of sleep irregularities in circulating leukocyte levels. Blood was collected from Control and CD individuals as per Helsinki Declaration from Morning (9 AM to 11AM) and Evening (7 PM to 9 PM) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Complete blood count analysis revealed a significant increase in circulating monocytes in CD individuals (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, 1.2 vs 2.5 x 10\u003csup\u003e5\u003c/sup\u003e cells/mL; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, unpaired t-test), accompanied by reduced total WBC (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and lymphocyte counts (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Next, we compared the differential increase in leukocyte number from morning to evening timepoints. Differential monocyte counts exhibited a disrupted morning-to-evening variation in CD individuals (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating altered diurnal distribution (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). These changes are subtle and warrant a deeper investigation into the transcriptomic signature to decode the role of circadian regulators in monocyte trafficking.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMonocytes rely on the dynamic expression of chemokine receptors for their trafficking and circulation. Monocytes that are isolated from blood are sensitive to external stimuli and differentiate into monocyte derived macrophages. Therefore, we isolated untouched monocytes that are pure, label free and versatile for gene expression. Chemokine receptors (CXCR4 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) \u0026amp; CCR2) and clock gene (BMAL1 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) \u0026amp; CLOCK (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001)) revealed a significantly lower expression in control volunteers as compared to CD after normalization with Actin protein expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD, E). Perturbations in circulating monocytes are regulated by chemokine receptors and our results further indicate a clear association between chemokine and Bmal1 downregulation in control volunteers (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD, E). However, these changes were preliminary observations in self-reported sleep disturbed individual that are hypothesis generating and warranted a deeper investigation. We acknowledge several limitations of the human data. First, the sample size (n\u0026thinsp;=\u0026thinsp;20) is modest, and the findings should be considered preliminary. Second, sleep disruption was assessed by self-report rather than objective measures such as actigraphy, which may introduce reporting bias. Third, the observed correlations do not establish causality. Larger, longitudinal studies with objective sleep monitoring are needed to validate these findings.\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:Differnetial\\:Monocyte\\:Count=Evening\\:Mono.\\:Counts-Morning\\:Mono.\\:Counts$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCircadian desynchrony disrupts the monocyte trafficking in mice\u003c/h3\u003e\n\u003cp\u003eWe had examined whether diurnal oscillations in monocyte trafficking were altered due to Chronodisruption in C57BL/6J mice. The diurnal trafficking of CD11b\u003csup\u003e+\u003c/sup\u003e lymphocytes, CD11b\u003csup\u003e+\u003c/sup\u003eLy6C\u003csup\u003e\u0026minus;\u003c/sup\u003e non-classical monocytes and CD11b\u003csup\u003e+\u003c/sup\u003eLy6C\u003csup\u003e+\u003c/sup\u003e classical monocytes was evaluated to understand the homeostatic myeloid release of immune cells from bone marrow into blood in CD. Monocytes from myeloid compartments (blood, bone marrow and spleen) were isolated from control and CD mice (n\u0026thinsp;=\u0026thinsp;3 per timepoint per group) at 5 intervals (ZT0, 6, 12, 18 and 24) during 24hrs. Food intake, water intake and body weight were recorded during the CD protocol and organ weight was taken post euthanasia and liver histology was performed (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e Extended Data 1D, E)Diurnal changes in myeloid compartments were analyzed using flow cytometry (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Gating strategy for each of the key compartment is given in extended data (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e Extended Data 1A-C).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eChronodisruption induced a measurable phase shift in the diurnal oscillations of CD11b⁺ lymphocytes and CD11b⁺Ly6C⁻ non-classical monocytes, shifting peak abundance from the inactive to the active phase across bone marrow, blood, and spleen (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB\u0026ndash;E). Bone marrow monocyte abundance showed no significant difference between groups (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05, two-way ANOVA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, D). Homeostatic myeloid release of Ly6C\u003csup\u003e+\u003c/sup\u003e monocytes from bone marrow was observed at ZT6 which is in consensus with activity period of mice and already published literature. Ly6C\u003csup\u003e+\u003c/sup\u003e monocytes percentage peaked in bone marrow during the active period (ZT12-ZT24) in control mice whereas; in CD mice a single peak was recorded at ZT 18 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, D). Our results demonstrate a consistent increment (ZT12-ZT18) in Blood Ly6C\u003csup\u003e+\u003c/sup\u003e monocytes percentage of CD mice as compared to a single peak at ZT12 in control (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, C). Consinor analysis was performed to quantify the amplitude and peak time. Similar observations were recorded wherein Ly6C\u003csup\u003e+\u003c/sup\u003e monocytes shown a peak shift (p\u0026thinsp;=\u0026thinsp;0.002) and change in amplitude (p\u0026thinsp;=\u0026thinsp;0.0005) in circulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e Extended Data 2A).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAmongst the myeloid compartments, spleen recorded significant changes in diurnal oscillations and net abundance in CD group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, E). Spleen plays a critical role by acting as a significant reservoir for storage and rapid deployment to sites of inflammation. Our data shows a significant accumulation of Ly6C\u003csup\u003e+\u003c/sup\u003e monocytes (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in control spleen during the day/inactive phase (ZT0-ZT12 and peak at ZT6) followed by a significant decrement/release in the night/active phase (ZT18) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) which is in agreement with published literature. However, CD Ly6C\u003csup\u003e+\u003c/sup\u003e monocytes were reported to migrate more in spleen with peak accumulation at two different time points (ZT6 and ZT18) in contrast to a single peak (ZT6) in control (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, E).\u003c/p\u003e\n\u003ch3\u003ePhenotypic shifts in circulating monocytes due to Chronodisruption\u003c/h3\u003e\n\u003cp\u003eWe had investigated the abundance of each of Monocyte subsets that are involved in inflammation to understand whether CD promote a specific phenotypic differentiation. The gating strategy for the same has been given in (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e Extended Data 1A). The diurnal abundance of CD11b\u003csup\u003e+\u003c/sup\u003eLy6C\u003csup\u003e+\u003c/sup\u003eCD86\u003csup\u003e+\u003c/sup\u003e monocytes and CD11b\u003csup\u003e+\u003c/sup\u003eLy6C\u003csup\u003e+\u003c/sup\u003eCD163\u003csup\u003e+\u003c/sup\u003e monocytes was studied using flow cytometry wherein; significant CD86\u003csup\u003e+\u003c/sup\u003e/CD163\u003csup\u003e+\u003c/sup\u003e abundance was recorded in CD group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF-H). The CD86\u003csup\u003e+\u003c/sup\u003e numbers peak at ZT12 and were consistently higher in control group whereas; the CD163\u003csup\u003e+\u003c/sup\u003e levels peaked at ZT18 indicative of a homeostatic rhythm (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF-H). CD group showed a relative decrement in CD86\u003csup\u003e+\u003c/sup\u003e monocytes and a significant increase in CD163\u003csup\u003e+\u003c/sup\u003e monocytes (p\u0026thinsp;=\u0026thinsp;0.0001) at ZT18. These findings suggest that Chronodisruption is associated with a shift toward a CD163⁺-enriched monocyte phenotype in circulation, consistent with an activated immune profile.(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e)\u003c/p\u003e\n\u003ch3\u003eRegulatory role of Bmal1 in Clock-chemokine interactions in monocytes\u003c/h3\u003e\n\u003cp\u003eMonocyte trafficking and migration is attributed to the diurnal interactions in chemokine receptors and its ligands. CD was able to significantly alter the diurnal oscillation of Ly6C\u003csup\u003e+\u003c/sup\u003e monocytes and therefore the intracellular oscillations in clock-chemokine expression was studied to understand the basis of altered monocyte trafficking. To validate the Chronodisruption due to CD protocol via BMAL1 and CLOCK protein oscillations in liver (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e Extended Data 3A). Untouched monocytes were isolated from blood, spleen and bone marrow at 6h intervals for a 24h period using negative selection based magnetic separation kits. Cosinor analysis records a consistent shift in oscillations, peak time and amplitude due to CD treatment. (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e Extended Data 4A).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCirculating monocytes recorded upregulation of BMAL1 and CLOCK proteins (p\u0026thinsp;=\u0026thinsp;0.0001) at ZT18 in CD group that was inverse to the control group. The chemokines CXCR4 (p,0.05) and CCR2 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) also recorded a concomitant increase at ZT18 in CD group with no significant peak recorded in the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, C). These results indicate an association between altered clock-chemokine oscillations and changes in circulating monocyte activation. Cosinor analysis also showed a similar pattern and confirmed cyclicity in the protein oscillations (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e Extended Data 4B). Further, we checked the clock-chemokine oscillations in spleen. The CD group recorded significantly higher levels of BMAL1, CLOCK, CXCR4 and CCR2 at ZT18 and ZT24 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB, D). Observations imply to the regulatory role of photoperiodic shifts. CCR2 showed a significant increase in CD monocytes. Single peak observed in CCR2 oscillations corroborated with increased monocyte counts reported at ZT18 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB, D).\u003c/p\u003e\n\u003ch3\u003eCircadian oscillation of survival, proliferation and chemotaxis genes are altered by CD\u003c/h3\u003e\n\u003cp\u003eChemokine receptors expressed on the surface of monocytes are activated by its respective ligands secreted by various tissues in the circulation. Receptor-ligand binding leading to the phosphorylation of CXCR4 leading to activation of downstream signaling cascade wherein; the chemotaxis pathway is an integral part of the signaling cascade. We had investigated the effects of CD on chemotaxis pathway that play a role in monocyte diapedesis/extravasation. The PI3K-Akt pathway in monocytes is crucial for survival, growth and inflammatory responses whereas; CDC42 and RAC1 regulate actin polymerization and morphological changes that perquisite before extravasation. We checked the expression of PI3K, AKT, CDC42 and RAC1 in circulating monocytes at every 6h, for 24h (from ZT0-ZT18). CD monocytes exhibited a\u0026thinsp;~\u0026thinsp;4-fold increase in PI3K expression compared with controls (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD). Interestingly, AKT-1 expression was significantly reduced at ZT6, ZT18, and ZT24 relative to control levels (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; normalized to β-actin) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, B). Monocytes adapt an amoeboid shape to pass through the endothelial cells into the extracellular matrix and CDC42 and RAC1 mediated F-actin to G-actin polymerization is imperative for migration. In control monocytes, CDC42 was upregulated from ZT12 to ZT24 indicating increased migration of monocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, B).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFinally, mechanistic association to our findings were recorded by Bmal1 knockdown experiment, we transfected THP-1 monocyte derived macrophages with siBmal1 siRNA and collected RNA samples every 6h for a 24h period (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). Timepoint based oscillations of candidate genes of Clock-Chemokine and Chemotaxis pathways revealed that siBmal1 administration causes downregulation of Cxcr4 and Ccr2 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Further, the downstream signaling pathway comprising of Pi3k, Akt1, mTor, Rac1 and Cdc42 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significantly downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eLowered Bmal1 expression results in downregulation of chemokine receptor in monocyte derived macrophages\u003c/h2\u003e \u003cp\u003eTo establish a functional relevance of Bmal1 in regulating chemokine expression, we wanted to explore the effects Bmal1 knockdown on THP-1 monocyte derived macrophages. THP-1 human monocytes were differentiated into macrophates using phorbol-12-myristate-13-acetate (PMA 50\u0026micro;M) and were transfected with small interfering RNA (siRNA) for Bmal1(siBmal1). The one without a functional binding site for human genome served as a negative control (siNC) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). BMAL1 knockdown at two siRNA concentrations (15 nM and 25 nM) reduced CXCR4 expression by ~\u0026thinsp;50% and CCR2 by ~\u0026thinsp;60% relative to control cells (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). as evidenced by the immunoblots (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, B). Further, we report that similar reduction was also observed in mRNA transcripts of Bmal1, Cxcr4 and Ccr2 genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC), thus validating the role of Bmal1 in regulating chemokine receptor expression.\u003c/p\u003e \u003cp\u003eBmal1 is a known transcription factor regulating rhythmic expression of genes by binding to the E-box enhancer elements in the promoter regions. Integration of publicly available ChIP-seq dataset demonstrates BMAL1 occupancy at regulatory regions of \u003cem\u003eCXCR4\u003c/em\u003e and \u003cem\u003eCCR2\u003c/em\u003e, supporting a transcriptional regulatory relationship that is further functionally validated by BMAL1 knockdown. To determine the association between BMAL1 and CXCR4, we used ChIP-Atlas database to integrate previously published ChIP-seq experiments and, to test the occupancy of BMAL1 in Cxcr4 \u0026amp; Ccr2 gene. Integrative genomic viewer plots revealed a significant binding of Bmal1 at an enhancer region (5\u0026rsquo; CATGTG 3\u0026rsquo;) 17kbp away from transcription start site (TSS) of Cxcr4 gene (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF, G) suggesting that Bmal1 binds to the Cxcr4 promotor.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCircadian control of monocyte homing via upregulation of CCR2-CCL2 axis.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eMonocytes trafficking is a multifactorial process because of its regulation via intra-cellular (Clock-chemokine-chemotaxis pathways) and extra-cellular signals (melatonin, corticosterone and chemokines). Untouched monocytes isolated using negative magnetic separation were stained with CFSE-FITC dye to achieve long term multi-generational staining (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). CFSE-FITC stained untouched monocytes from control (Non-Manipulated) and CD (Manipulated) groups were adoptively transferred into control or CD mice and allowed to migrate for 24h. At the end of incubation period, percentage of adoptively transferred monocytes in blood, bone marrow, spleen and liver were quantified using flow cytometry (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). The gating strategy for the same has been given in (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e Extended Data 1E). Our data showed, no significant change in abundance of adoptively transferred monocytes in various tissues between C\u0026thinsp;+\u0026thinsp;N, C\u0026thinsp;+\u0026thinsp;M and CD\u0026thinsp;+\u0026thinsp;M groups. Blood and bone marrow recorded a non-significant increment in FITC+ monocytes in CD\u0026thinsp;+\u0026thinsp;M group whereas, spleen and liver recorded higher abundance in C\u0026thinsp;+\u0026thinsp;N group (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e Extended Data 1B).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTrafficking of manipulated (M) and non-manipulated (N) monocytes under experimentally induced inflammatory conditions (carbon tetrachloride; CCL4 induced chemical hepatotoxicity) was studied in mice (n\u0026thinsp;=\u0026thinsp;6 per group). Effects of low and high doses (1ml/kg B.W. \u0026amp; 3ml/kg B.W. I.P.) were observed till 72 hours wherein; no mortality was recorded. Both the doses showed significantly high titers of AST and ALT in serum and liver damage at the end of 48h (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e Extended Data 1A-D). After 24h of intraperitoneal injection of CCL4, mice were intravenously administered with CFSE-FITC tagged CD (C\u0026thinsp;+\u0026thinsp;M and CCL4\u0026thinsp;+\u0026thinsp;M) and control monocytes (C\u0026thinsp;+\u0026thinsp;N and CCL4\u0026thinsp;+\u0026thinsp;N). FITC+ monocytes from blood, spleen, bone marrow and liver were analyzed using flow cytometry (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). Gating strategy for detection of adoptively transferred monocytes is included in the extended data (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e Extended Data 1E). Histopathological analysis revealed significant infiltration of monocytes in liver of CCL4\u0026thinsp;+\u0026thinsp;N and CCL4\u0026thinsp;+\u0026thinsp;M groups compared to control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e Extended Data 1C, D). CCL4 treated groups showed significant ballooning, inflammatory damage and immune cell accumulation as compared to control groups. Both the groups also recorded elevated titers of AST and ALT (p\u0026thinsp;=\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e Extended Data 1C, D).\u003c/p\u003e \u003cp\u003eBlood did not record any significant changes in FITC+ monocytes from all the groups. However, the highest abundance of adoptively transferred monocytes was recorded in blood as compared to other compartments (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). We observed significantly higher percentage of adoptive monocytes migrating to bone marrow in CCL4\u0026thinsp;+\u0026thinsp;M (p\u0026thinsp;=\u0026thinsp;0.01) group as compared to CCL4\u0026thinsp;+\u0026thinsp;N (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). Higher number of monocytes migrating towards the bone marrow can be attributed to significantly higher expression of CXCR4 receptors observed in our study. Further, spleen being the essential site of deployment of monocytes under inflammatory condition, we observed that CD monocytes (C\u0026thinsp;+\u0026thinsp;M) showed significant migration into spleen (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). This also underlines the fact that under normal conditions monocytes move to spleen. Control monocytes (CCL4\u0026thinsp;+\u0026thinsp;N; p\u0026thinsp;=\u0026thinsp;0.0001) migrate more towards spleen as compared to CD (CCL4\u0026thinsp;+\u0026thinsp;M; p\u0026thinsp;=\u0026thinsp;0.0001) whose abundance could be tracked in liver. 3 fold higher number of monocytes (p\u0026thinsp;=\u0026thinsp;0.0001) migrated into the inflamed liver as compared to its control. However, no change was observed for adoptively transferred control monocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). These results highlight the fact that, under homeostatic conditions both the monocytes recorded identical migratory pattern. Experimentally induced inflammation causes desensitization of CXCR4 accounting for a higher number of monocytes migrating into the inflamed liver. Such a boost in migratory behavior of CD monocytes can be attributed to higher expression of CCR2 chemokine receptor due to an upregulation of Bmal1 protein (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-D). Our study provides evidence supporting a role for circadian desynchrony-mediated upregulation of Bmal1 in monocytes that eventually culminates in augmented homing towards an inflamed target.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur findings consolidate a model wherein; the core circadian regulator Bmal1 acts as a transcriptional regulator in monocytes, directly regulating Cxcr4 and Ccr2 to enforce a rhythmic diurnal constraint on chemotaxis\u0026mdash;a checkpoint that is imperative during inflammatory challenge. Shift-work cohorts have been reported to exhibit significant, chronic elevations in total monocyte and lymphocyte counts (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). We had observed a profound elevation in morning and evening monocyte, WBC, and lymphocyte counts, characterized by upregulated monocytic clock gene and chemokine expression. The core clock gene Bmal1 broadly synchronizes immune responses with circadian environmental signals (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Elevated Bmal1 levels can occur through promoter methylation and via coordinated breakdown of its negative regulators PER/CRY (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Further, monocytes are highly sensitive to photoperiodic perturbations and respond to chronic sleep deprivation with heightened Bmal1 expression.(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) In our study, elevated Bmal1 levels in monocytes of sleep deprived individuals can be attributed to the said mechanism but the role of Bmal1 in the regulation of chemokine receptors is not known. We hypothesize that sleep disruption is associated with altered circadian gene expression in circulating monocytes that can possibly disrupt chemokine oscillations and impact their homing.\u003c/p\u003e \u003cp\u003eIn experimental mice models, myeloid-specific Bmal1 deletion has yielded complex phenotypes, including altered monocyte recruitment in atherosclerosis, regulation of NLRP3 inflammasome activation, enhanced NF-κB\u0026ndash;mediated inflammatory responses, and modulation of ferroptosis and phagocytosis.(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). These reports support a context-dependent, dual role for Bmal1 in macrophage biology. However, studies relying on complete genetic ablation require cautious interpretation, as they may not fully capture the subtle circadian perturbations observed in human pathophysiology, such as chronic sleep deprivation and shift work. Accordingly, the chronodisruption (CD) model employed in our study more faithfully recapitulates the gradual and sustained CD experienced by shift workers, providing a physiologically relevant framework to examine immune consequences. We found that CD altered the diurnal oscillation of inflammatory monocytes (Ly6C⁺) in circulation complemented by coordinated changes in clock genes and chemokine receptors. This was further exemplified into a disrupted circadian rhythm in monocytes that affected their homeostatic release from the bone marrow and caused retention in spleen. These findings are in sync with other research groups that report CD mediated rhythmic activation of chemokine signalling, inflammatory pathways such as NF-κB, and cellular egress from hematopoietic reservoirs(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo establish regulatory role of Bmal1 in chemokine expression, our study of Bmal1 KD in THP-1 monocyte-derived macrophages had resulted in significantly lowered Cxcr4 and Ccr2. Further, the in silico chip analysis had identified a sequence upstream of Cxcr4 \u0026amp; Ccr2 promoter that had an affinity for binding to the Bmal1\u0026ndash;Clock heterodimer. Both these findings provide compelling evidence on role of Bmal1 in regulating chemokine expression in monocytes. The regulation of chemokines represents a critical integration point for diverse signals (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) and our work establishes Bmal1 as a important paradigm for Cxcr4 and Ccr2 expression.\u003c/p\u003e \u003cp\u003eTo establish evidence in support our hypothesis, normal (N) and CD-manipulated (M) monocytes were adoptively transferred in mice with healthy or an inflamed liver (carbon tetrachloride; CCL4 treated). Though, there were no significant changes observed in homing scores of N and M monocytes in healthy mice, a 3 fold increase was recorded in the latter. This amounts to a critical divergence in tropism of M monocytes in response to an inflammatory challenge that can be attributed to an upregulated Bmal1-chemokine axis.\u003c/p\u003e \u003cp\u003eIn a study involving developmental BMAL1 KO, the circadian monocyte trafficking was found to cause CCL2 upregulation (Nguyen et al., 2013). The said observation was implicated as the cause for augmented monocyte trafficking. It may be noted that, the monocyte-autonomous CCL2 secretion model may be context-dependent and may reflect an artificial scenario wherein developmental knockout of BMAL1 unmasks CCL2 expression. This scenario differs from the physiological chronodisruption reported in our study involving Cxcr4 and Ccr2 upregulation mediated increased monocyte trafficking. Our data suggests that prior interpretations of BMAL1\u0026rsquo;s role in immunity may require re-evaluation in context of shift work, jet lag, or metabolic diseases.\u003c/p\u003e \u003cp\u003eIn summary, this study establishes that the circadian regulator BMAL1 acts as a key regulator of monocyte chemokine receptors viz. CXCR4 and CCR2, to enforce rhythmic control over their chemotaxis. Chronic sleep deprivation disrupts this checkpoint, elevating Bmal1 that drives pathological chemokine receptor expression. Consequently, monocytes exhibit aberrant tissue trafficking and splenic retention, under chronodisruptive conditions. This Bmal1-driven reprogramming, augments monocytes toward inflamed tissues upon a challenge thus positioning the monocyte-Bmal1-chemokine axis as a critical effector of Chronodisruption.\u003c/p\u003e\n\u003ch3\u003eLimitations\u003c/h3\u003e\n\u003cp\u003e(i) While we integrate human observations with mouse and cellular models to provide translational insight, the human component is constrained by sample size (n\u0026thinsp;=\u0026thinsp;20) and reliance on self-reported sleep measures. Use of actigraphy and larger cohorts would strengthen the human findings. (ii) Adoptive transfer shows altered homing to inflamed liver, the relevance of this reprogramming to specific chronic inflammatory diseases (e.g., atherosclerosis or metabolic syndrome) requires testing in dedicated disease models. Despite these limitations, our multi-system approach establishes that circadian disruption elevates BMAL1 in monocytes, driving chemokine receptor expression and biasing monocytes toward inflamed tissues\u0026mdash;a phenotype absent in homeostasis\u0026mdash;thus identifying the monocyte-BMAL1-chemokine axis as a potential target in sleep-disruption-associated inflammation.\u003c/p\u003e "},{"header":"Methods","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003cp\u003eHuman Monocyte study\u003c/p\u003e \u003cp\u003eHealthy male and female volunteers without any known comorbidities were recruited for the study. All participants completed a detailed questionnaire (Supplementary Table\u0026nbsp;3) assessing their weekly sleep patterns. Based on questionnaire responses, volunteers were categorized into two groups: control (C) and sleep-disrupted/chronodisrupted (CD). A total of 20 participants (male:female ratio 12:8; age range 21\u0026ndash;40 years) were enrolled according to predefined inclusion and exclusion criteria (Supplementary Table\u0026nbsp;3). None of the participants had a known history of chronic or long-term medical disorders. Written informed consent was obtained from all participants prior to sample collection. Peripheral blood samples were collected by a trained laboratory technician under the supervision of a certified pathologist as per the standard clinical procedures at BlueCross Pathology Laboratory, Makarpura, Vadodara (IMA No. 1093). Blood collection was performed at two time points: morning (09:00\u0026ndash;11:00 h) and evening (19:00\u0026ndash;21:00 h), with a one-week interval between consecutive sampling sessions. From each collection, 500 \u0026micro;L of blood was used for complete blood count and total lipid profile analysis. Untouched monocytes were subsequently isolated from the remaining sample using the Dynabeads\u0026trade; Untouched Human Monocyte Isolation Kit (Invitrogen, Thermo Fisher Scientific, USA), according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e \u003cp\u003eCell line and culture\u003c/p\u003e \u003cp\u003eMonocytic Leukemia cell line THP-1 was a kind gift from Dr. Arunika Mukhopadhaya, IISER, Mohali. THP-1 cells were maintained in complete Rosewell Park Memorial Institute- 1640 medium (Gibco) supplemental with 1x Antibiotic-Antimycotic Cocktail (Himedia Laboratories, Mumbai, India), 10% fetal bovine serum (Value FBS, Thermo Fisher Scientific). Cells were regularly tested for mycoplasma, and all the experiments were performed between passage number 12 and 19. A new aliquot of the cell line was thawed and cultured consecutively for \u0026lt;\u0026thinsp;2 months. THP-1 monocytes were differentiated into Human monocyte derived macrophages as described previously (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) and 50% Horse serum (Horse Serum, Thermo Fisher Scientific) was used to resynchronize the clock before setting up of each biological replicate.\u003c/p\u003e \u003cp\u003esiRNA based Bmal1 Knockdown\u003c/p\u003e \u003cp\u003eTHP-1 monocytes were differentiated into monocyte derived macrophages seeded onto a 24 well plate at concentration of 1 x 105 cell/well and were incubated in complete RPMI-1640 medium (Gibco, Thermo Fisher Scientific) for 24 hours. Later cells were transfected with two different concentrations of siRNA for Bmal1 (si-Bmal1) and negative control (si-NC) (Qiagen Germany) having no sequential binding sites in human genome using Lipofectamine 3000 (Thermo fisher Scientific, USA) transfection reagent. siRNA and transfection reagents were diluted in a low protein, serum reduced cell culture medium Opti-MEM (Thermo fisher Scientific, USA), incubated for 20 mins for the formation of RNA-reagent complex and slowly layer on to differentiated monocyte derived macrophages. Incomplete media was added to make up the volume of the complete system up to 250ul and incubated for 24 hours under 5% CO2.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eRT-PCR\u003c/h2\u003e \u003cp\u003eTotal RNA was purified TRizol reagent (Thermo fisher scientific,USA) following manufacturers protocol. Isolated RNA was quantified using Take3 microvolume plate (Agilient Biosciences) used with Synergy HTX microplate reader. 1000ng of total RNA was reverse transcribed using BIORAD cDNA synthesis Kit (Biorad, USA). cDNA samples were then subjected to quantitative real-time PCR analysis using Hi-SYBR Master mix (Himedia Laboratories, India) following manufacturer\u0026rsquo;s instructions on a Qunatstudio 5 Real time PCR (Invitrogen). 18s rRNA was used a housekeeping gene for normalization of the samples. Primers specific for each gene were synthesized by Eurofins, India and specific sequences are available in Supplementary Table\u0026nbsp;2.(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eWestern Blotting\u003c/p\u003e \u003cp\u003eCollected cells and tissues were lysed in 1X RIPA buffer on ice for 30 min, with protease and phosphatase inhibitors tablets (Roche, Sigma). Lysates were centrifuged at 12,000g for 5 min at 4\u0026deg;C to obtain the supernatant. Protein content was then quantified by bicinchoninic acid assay (Biorad, USA) and diluted to a final concentration of 1\u0026ndash;2 \u0026micro;g \u0026micro;l\u0026ndash;1. After the addition of 5\u0026times; SDS\u0026ndash;PAGE loading buffer (Himedia Laboratories, India), samples were boiled at 95\u0026deg;C for 10 min, resolved via SDS\u0026ndash;PAGE and transferred to a PVDF membrane (Biorad, USA). Membranes were blocked in Pierce Protein Free Block Buffer (Thero Fisher Scientific, USA) at room temperature for 1 h and subsequently incubated with the primary and secondary antibodies. Antibodies Bmal1 (1:1000), Clock (1:000) and anti-rabbit-HRP conjugated (1:2000) were purchased from Invitrogen, Thermo fisher, USA. The antibodies Pi3k (1:1000), Akt-1 (1:1000), cDC42 (1:1000), Cxcr4 (1:1000), Ccr2/Cd-192 (1:1000) and Actin (1:1500) were purchased from Elabsciences Bionovation Inc. Blot signals were detected using a Chemidoc Touch (Biorad, USA) or were developed on X-ray films in a dark room.\u003c/p\u003e \u003cp\u003eHuman Monocyte Isolation\u003c/p\u003e \u003cp\u003ePeripheral blood mononuclear cells (PBMC) were prepared by centrifugation on a Hisep LSM 1077 (LS001; HiMedia Laboratory Pvt. Limited, India). Untouched monocytes were isolated using Invitrogen Dynabeads Untouched Human Monocyte Isolation Kit (Thermo fisher Scientific, USA) according to manufacturer\u0026rsquo;s protocol. Isolated monocytes were subjected to downstream gene expression analysis.\u003c/p\u003e \u003cp\u003eAnimals\u003c/p\u003e \u003cp\u003eC57BL/6J WT mice (10\u0026ndash;12 weeks old) were procured from Advanced center for treatment research and education in cancer, Mumbai, India. 87 male mice were housed and routinely handled in Animal House facility, Department of Zoology, Faculty of Science, The Maharaja Sayajirao University of Baroda, Vadodara, Gujarat, India as per CCSEA guidelines. All mice were fed with standard mice chow. Animal protocols were reviewed and approved (MSU-Z/IAEC08/01-2024) by the Institutional Animal Ethical Committee (IAEC), Department of Zoology, Faculty of Science, The Maharaja Sayajirao University of Baroda, Vadodara, Gujarat, India. All the protocols were performed as per ARRIVE guidelines and mice were euthanized; samples were collected as per IAEC and CCSEA guidelines.\u003c/p\u003e \u003cp\u003eAnimal Experiments\u003c/p\u003e \u003cp\u003eAfter two weeks of acclimatization, 10\u0026ndash;12 weeks old mice were randomly divided into two groups (N\u0026thinsp;=\u0026thinsp;25; n\u0026thinsp;=\u0026thinsp;5/timepoint). Group I: Control mice fed with standard chow diet and maintained in LD 12:12; Group II: Chronodisruption (CD) mice fed on standard chow diet and subjected to phase advance-phase delay photoperiod as described previously (Ref). Mice were fasted for 8\u0026ndash;10 hours and blood, spleen, bone marrow and liver were harvested at different timepoints (ZT0, 6, 12, 18 \u0026amp; 24). The samples were divided into 4 parts and stored for flow cytometry, in RNA Latter (Thermo fisher scientific, USA), in 4% PFA (for histopathology) or in -80\u0026deg; C (for immunoblots). Single cell suspension of spleen and liver was prepared by passing through 40-micron cell strainer (Geneaxy, India) followed by fixation with 4% paraformaldehyde. Sample were analyzed using BD FACS ARIA II.\u003c/p\u003e \u003cp\u003eThe second in vivo experiment was performed to standardize the operational dose of CCL4, wherein mice were acclimatized for two weeks and later, randomly divided into 4 groups (n\u0026thinsp;=\u0026thinsp;3/group). Group I: Control (0.9% ns), Group II: Vehicle control (Olive Oil; Sigma Aldrich), Group III: CCL4 Low dose (1ml/kg; 1:4 dilution in olive oil) Group IV: CCL4 High dose (5ml/kg; 1:4 dilution in olive oil). Group I, II, III, IV received a single intraperitoneal injection of ns, olive oil or CCL4. Cage side observations were recorded for 72 hours to document behavioural perturbations and survival. Later, mice were sacrificed and, blood, liver and spleen were collected at 24-hour and 48-hour time points.\u003c/p\u003e \u003cp\u003eThe third in vivo study involved monitoring the monocyte homing in C57BL/6J mice. After the phase of acclimatization as mentioned above, the mice were randomly divided into 05 groups viz. Group I: Sham (ns i.v.) Group II: Control recipient\u0026thinsp;+\u0026thinsp;normal monocytes from healthy donor (C\u0026thinsp;+\u0026thinsp;N), Group III: Control recipient\u0026thinsp;+\u0026thinsp;manipulated monocytes from CD donor (C\u0026thinsp;+\u0026thinsp;M), Group IV: CCL4\u0026thinsp;+\u0026thinsp;normal monocytes (CCL4\u0026thinsp;+\u0026thinsp;N) and Group V: CCL4\u0026thinsp;+\u0026thinsp;manipulated monocytes (CCL4\u0026thinsp;+\u0026thinsp;M). The doses of (ns, olive oil or CCL4) were injected intraperitoneally and cage side observations were recorded for 24 hours. Later, CFSE tagged monocytes (N or M) were injected intravenously (in C or CCL4 treated mice). After 48 hours, mice were anesthetized for collection of blood, bone marrow, spleen and liver.\u003c/p\u003e \u003cp\u003eMouse Monocyte isolation\u003c/p\u003e \u003cp\u003eMononuclear cells were isolated (at various time points as mentioned above) using Hisep LSM 1084 (LS003; HiMedia Laboratory Pvt. Limited, India). Later, the untocuhed monocytes were isolated using a MojoSort Mouse monocyte isolation kit (Biolegend) and were subjected to downstream flow cytometry and gene expression analysis.\u003c/p\u003e \u003cp\u003eFlow cytometry analysis\u003c/p\u003e \u003cp\u003eA timepoint based flow cytometry analysis was carried to understand monocyte migration in bone marrow, blood and spleen following photoperiod induced chronodisruption. Blood, bone marrow and spleen were collected as mentioned above and a single cell suspension from blood, and bone marrow was subjected to Ammonium-chloride-potassium (ACK) lysis buffer for 10 mins. The cell pellet was washed with PBS twice and resuspended in PBS. Single-cell suspension from spleen was prepared by mechanically disrupting the tissue using a syringe plunger through a 40-micron cell strainer and ACK lysis was carried out by same process. Fc receptor from single cell suspension from blood, bone marrow and spleen were blocked using Anti-mouse CD16/32 Antibody (2.4G2) (Elabsciences, USA). Cell suspension was stained for 30 mins at 4\u0026deg;C with E-lab Fluor Violet 540 Anti-mouse Ly6C (E-AB-F1121T3), PE/Cyanine 7 Anti-mouse CD11b (E-AB-F1081H), FITC Anti-mouse CD86 (E-AB-F0994C) and APC Anti-mouse CD163 (E-AB-F1295C); subsequently washed with cell staining buffer (E-CK-A107) and fixed with 4% PFA (for 5mins). Excess PFA was removed by PBS wash and resuspension in cell staining buffer.\u003c/p\u003e \u003cp\u003eA single timepoint (ZT12) collection of blood, bone marrow, spleen and liver was done for monocyte homing studies. Single cell suspension of blood, bone marrow and spleen were prepared as described above. Liver (approx 50 \u0026micro;g) was cut and incubated in collagenase type IV for 15 mins at 37\u0026deg;C. A single cell suspension was prepared by mechanically disrupting the tissue using a syringe plunger and passed through 40-micron cell strainer. ACK lysis protocol was done as mentioned above. The samples were analyzed using BD FACS Aria II and FlowJo was used for downstream analysis.\u003c/p\u003e \u003cp\u003eCFDA, SE staining and Monocyte adoptive transfer\u003c/p\u003e \u003cp\u003eDonor mice: Control or chronodisrupted groups served as the donor mice. Monocytes were collected from the control (N; Normal monocytes) or chronodisrupted mice (M; Manipulated monocytes) as described previously using MojoSort Mouse monocyte isolation kit. CFDA, SE dye was selected due to their superior performance in terms of bright and uniform staining of all cells, longer retention time and minimal toxicity. Untouched monocytes were stained, washed twice with PBS and a cell count of 3 x 106 cells/100\u0026micro;L was used for further study.\u003c/p\u003e \u003cp\u003eRecipient mice: Control (olive oil i.p.) or CCL4 (injected with 1ml/kg CCL4 in 1:4 dilution in olive oil, i.p.) were used for this study. These mice received an adoptive transfer of monocytes (received from donor mice: normal (N) or manipulated (M) (100\u0026micro;L/ mice) through tail vein injection following lamp-based vasodilation. Post 24 hour of adoptive transfer, mice were euthanised and monocyte homing was studied in blood, bone marrow, spleen and liver using flow cytometry.\u003c/p\u003e \u003cp\u003eLiver function test\u003c/p\u003e \u003cp\u003eCirculating liver enzymes (AST, ALT, and ALP) and serum lipid profile parameters, including total lipids, total cholesterol, triglycerides, LDL, VLDL, HDL, cholesterol/HDL, and LDL/HDL ratios, were assessed using standard commercial diagnostic kits (Reckon Diagnostics, Vadodara, Gujarat, India).(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eLiver Histopathology\u003c/p\u003e \u003cp\u003eLiver samples (n\u0026thinsp;=\u0026thinsp;6/group) were autopsied, washed in PBS and fixed in 4% paraformaldehyde. Paraffin-embedded, liver sections (5 \u0026micro;m) were stained with haematoxylin and eosin (H\u0026amp;E) and photographed on Leica DM 2500 microscope. Qualitative evaluation focused on inflammatory foci, immune cell infiltration, sinusoidal alterations and disruption of hepatic cord organization were observed.(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll the data were analyzed in Prism 10 (GraphPad). Statistical test such as ANNOVA, student t-test were performed as indicated in the figure legends, and number of replicates are also provided. All error bars represent mean\u0026thinsp;\u0026plusmn;\u0026thinsp;S.D. Mice were randomly assigned to the treatment groups and number mice per group are as indicated. Data was presumed to be normally distributed. Statistical significance was defined as *P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ***P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, ****P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 vs Control, the individual\u003c/p\u003e \u003c/div\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData from this study is available upon request. Source Data is provided with this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eR.K., A.V., H.V. and R.V.D. conceived the project, designed the experiments, analyzed and interpreted the data. R.K., H.S., and R.V.D. wrote the paper. R. K., H.S., M.K., P.P., S.K., performed the human volunteer study. R.K. and H.S. performed all the \u003cem\u003ein vitro\u003c/em\u003e experiments. R.K., H.S., M.K., P.P., S.K. and S.J. performed the mouse experiments. R.K. initiated and performed the flow cytometry study, carried out the data analysis of monocyte trafficking and monocyte adoptive transfer studies. R.V.D. directed the study, interpreted the data and supervised the work.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to Ranjitsinh V. Devkar\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge the funding provided by the Department of Biotechnology, Ministry of Science \u0026amp; Technology, Government of India (BT/PR42042/MED/30/2323/2021 to R.V.D.). R.K. and H.V. were supported by LTMT Senior Research Fellowship, Lady Tata Memorial Trust Senior Research Fellowship. H.S. was supported by DBT BET Fellowship, Department of Biotechnology, Ministry of Science \u0026amp; Technology, Government of India. A.V. was supported by DST Purse Fellowship, Department of Science \u0026amp; Technology, Ministry of Science \u0026amp; Technology, Government of India. We also acknowledge the contribution by Mr. Bhaumik Jaiswal for the help rendenred during the study. We thank the technical staff of Flow Cytometry Shared Lab Facility, Gujarat Biotechnology Research Center, Gandhinagar, Gujarat, India for their excellent technical assistance. \u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFagiani F, Di Marino D, Romagnoli A, Travelli C, Voltan D, Mannelli LDC, et al. Molecular regulations of circadian rhythm and implications for physiology and diseases. 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Redox Biol. 2020;28.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"","lastPublishedDoi":"10.21203/rs.3.rs-8894070/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8894070/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eChronodisruption from shift work or sleep disruption is associated with inflammatory diseases, but the molecular pathways linking circadian disruption to aberrant immune cell trafficking remain unclear. Here, we identify a circadian-immune circuit wherein the core clock protein BMAL1 regulates monocyte homing by controlling chemokine receptors CXCR4 and CCR2. In sleep-disrupted individuals, we observed elevated monocyte counts alongside increased BMAL1 and chemokine receptor expression. Using a physiologically relevant murine model of chronic chronodisruption, we found that BMAL1 upregulation alters the diurnal rhythm of monocyte trafficking, leading to aberrant splenic retention and amplified chemokine-driven migratory signaling. ChIP-seq analysis revealed BMAL1 occupancy at enhancer regions of Cxcr4 and Ccr2, and its knockdown significantly attenuated their expression and associated PI3K\u0026ndash;CDC42/RAC1 signaling. Adoptively transferred monocytes from chronodisrupted mice showed no trafficking abnormalities in healthy recipients but displayed a biased migratory preference for inflamed liver tissue upon inflammatory challenge. Our findings identify the BMAL1\u0026ndash;chemokine axis as a regulator of monocyte trafficking and provide a mechanistic basis for heightened inflammatory responses under conditions of circadian disruption.\u003c/p\u003e","manuscriptTitle":"Circadian Clock protein Bmal1 drives inflammatory homing in monocytes via augmented Cxcr4 and Ccr2 axis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-18 04:31:29","doi":"10.21203/rs.3.rs-8894070/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":"7ca9a93b-9e55-43cf-8979-a6e2bcdb8ffc","owner":[],"postedDate":"February 18th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":63016583,"name":"Biological sciences/Immunology/Chemokines"},{"id":63016584,"name":"Biological sciences/Immunology/Innate immune cells/Monocytes and macrophages"}],"tags":[],"updatedAt":"2026-03-07T14:31:00+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-18 04:31:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8894070","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8894070","identity":"rs-8894070","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}