Hookworm genes encoding intestinal excreted-secreted proteins are transcriptionally upregulated in response to the host’s immune system

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Schwarz , View ORCID Profile Jason B. Noon , View ORCID Profile Jeffrey D. Chicca , Carli Garceau , View ORCID Profile Hanchen Li , View ORCID Profile Igor Antoshechkin , View ORCID Profile Vladislav Ilík , View ORCID Profile Barbora Pafčo , View ORCID Profile Amy M. Weeks , View ORCID Profile E. Jane Homan , View ORCID Profile Gary R. Ostroff , View ORCID Profile Raffi V. Aroian doi: https://doi.org/10.1101/2025.02.01.636063 Erich M. Schwarz 1 Department of Molecular Biology and Genetics, Cornell University , Ithaca, NY, 14853, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Erich M. Schwarz For correspondence: ems394{at}cornell.edu raffi.aroian{at}umassmed.edu Jason B. Noon 2 Program in Molecular Medicine, University of Massachusetts Chan Medical School , Worcester, MA, 01605, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Jason B. Noon Jeffrey D. Chicca 2 Program in Molecular Medicine, University of Massachusetts Chan Medical School , Worcester, MA, 01605, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Jeffrey D. Chicca Carli Garceau 2 Program in Molecular Medicine, University of Massachusetts Chan Medical School , Worcester, MA, 01605, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Hanchen Li 2 Program in Molecular Medicine, University of Massachusetts Chan Medical School , Worcester, MA, 01605, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Hanchen Li Igor Antoshechkin 3 Division of Biology and Biological Engineering, California Institute of Technology , Pasadena, CA, 91125, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Igor Antoshechkin Vladislav Ilík 4 Department of Botany and Zoology, Faculty of Science, Masaryk University , Kotlářská 267/2, 611 37 Brno, Czech Republic 5 Institute of Vertebrate Biology, Czech Academy of Sciences , Květná 8, 603 65 Brno, Czech Republic Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Vladislav Ilík Barbora Pafčo 5 Institute of Vertebrate Biology, Czech Academy of Sciences , Květná 8, 603 65 Brno, Czech Republic Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Barbora Pafčo Amy M. Weeks 6 Department of Biochemistry, University of Wisconsin-Madison , Madison, WI, 53706, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Amy M. Weeks E. Jane Homan 7 ioGenetics LLC , 301 South Bedford Street, Ste.1, Madison, WI, 53703, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for E. Jane Homan Gary R. Ostroff 2 Program in Molecular Medicine, University of Massachusetts Chan Medical School , Worcester, MA, 01605, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Gary R. Ostroff Raffi V. Aroian 2 Program in Molecular Medicine, University of Massachusetts Chan Medical School , Worcester, MA, 01605, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Raffi V. Aroian For correspondence: ems394{at}cornell.edu raffi.aroian{at}umassmed.edu Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Hookworms are intestinal parasitic nematodes that chronically infect ∼500 million people, with reinfection common even after clearance by drugs. How infecting hookworms successfully overcome host protective mechanisms is unclear, but it may involve hookworm proteins that digest host tissues, or counteract the host’s immune system, or both. To find such proteins in the zoonotic hookworm Ancylostoma ceylanicum , we identified hookworm genes encoding excreted-secreted (ES) proteins, hookworm genes preferentially expressed in the hookworm intestine, and hookworm genes whose transcription is stimulated by the host immune system. We collected ES proteins from adult hookworms harvested from hamsters; mass spectrometry identified 565 A. ceylanicum genes encoding ES proteins. We also used RNA-seq to identify A. ceylanicum genes expressed both in young adults (12 days post-infection) and in intestinal and non-intestinal tissues dissected from mature adults (19 days post-infection), with hamster hosts that either had normal immune systems or were immunosuppressed by dexamethasone. In adult A. ceylanicum , we observed 1,670 and 1,196 genes with intestine- and non-intestine-biased expression, respectively. Comparing hookworm gene activity in normal versus immunosuppressed hosts, we observed almost no changes of gene activity in 12-day young adults or non-intestinal 19-day adult tissues. However, in intestinal 19-day adult tissues, we observed 1,951 positively immunoregulated genes (upregulated at least two-fold in normal hosts versus immunosuppressed hosts), and 137 genes that were negatively immunoregulated. Thus, immunoregulation was observed primarily in mature adult hookworm intestine directly exposed to host blood; it may include hookworm genes activated in response to the host immune system in order to neutralize the host immune system. We observed 153 ES genes showing positive immunoregulation in 19-day adult intestine; of these genes, 69 had ES gene homologs in the closely related hookworm Ancylostoma caninum , 24 in the human hookworm Necator americanus , and 24 in the more distantly related strongylid parasite Haemonchus contortus . Such a mixture of rapidly evolving and conserved genes could comprise virulence factors enabling infection, provide new targets for drugs or vaccines against hookworm, and aid in developing therapies for autoimmune diseases. Introduction The hookworms Necator americanus , Ancylostoma duodenale , and Ancylostoma ceylanicum are parasitic nematodes that infect ∼500 million human beings, sickening them and lowering their economic productivity ( B ethony et al . 2006 ; T raub 2013 ; P ullan et al . 2014 ). Hookworms are remarkably long-lived parasites: an adult hookworm can feed off its human host for up to 18 years ( B eaver 1988 ; G ems 2000 ), and infection times of 1-5 years are common ( H oagland and S chad 1978 ). Hookworms achieve this partly by feeding on the host with enzymes optimized to digest host proteins ( R anjit et al . 2009 ), and partly by suppressing the immune systems of their hosts, which would otherwise kill or expel them quickly ( M aizels et al . 2018 ). Only one drug, albendazole, is commonly used and effective enough to be useful in mass drug administration against hookworm infections ( K eiser and U tzinger 2008 ; L oukas et al . 2016 ). However, human hookworms may be developing genetic resistance to this drug ( O rr et al . 2019 ; V laminck et al . 2019 ; W alker et al . 2021 ), as has already happened with dog hookworms ( V enkatesan et al . 2023 ). Moreover, even effective use of albendazole does not prevent endemic hookworms from reinfecting people ( J ia et al . 2012 ). An anti-hookworm vaccine would be an ideal way to suppress hookworm infections ( C ohen 2016 ), but no such vaccine exists, in part because we do not know which gene products mediating host-parasite interactions should be targeted as antigens ( Z awawi and E lse 2020 ). It is not yet certain how hookworms (or any other parasitic nematodes) dampen the host immune system, but many possible effectors of immunomodulation exist: secreted proteases ( R anjit et al . 2009 ; K nox 2012 ; P earson et al . 2012 ); secreted protease inhibitors ( M anoury et al . 2001 ; H artmann and L ucius 2003 ; K lotz et al . 2011 ); large gene families encoding diverse secreted proteins as antigenic decoys ( C antacessi et al . 2009 ; T ribolet et al . 2015 ); mimics of mammalian immune proteins ( L oukas et al . 2000 ; Y oshida et al . 2012 ); lipid immunomodulators ( H arnett et al . 2010 ; J ex et al . 2014 ; S hinoda et al . 2022 ); and secreted exosomes with anti-host miRNAs ( B uck et al . 2014 ; C oakley et al . 2017 ). These mechanisms are by no means exclusive; some or all of them could be working at once. Such complexity may have evolved over 350 million years, when vertebrates first colonized the land and became vulnerable to parasitic nematodes ( A nderson 1984 ; C lark 1994 ; Ds urette -D esset et al . 1994 ). Ignorance of how hookworms immunosuppress their hosts makes it challenging to devise vaccines against hookworm disease. It also hinders the possible use of hookworms as sources of new biological reagents against autoimmune diseases ( S mallwood et al . 2021 ; R yan et al . 2022 ), which appear to become more frequent with lower rates of helminth infection ( M aizels 2020 ). Hookworms and other parasitic helminths have long been known to excrete or secrete proteins into their hosts, and these excreted/secreted (ES) proteins have long been hypothesized, and in some cases demonstrated, to enable immunosuppression and virulence ( S tirewalt 1963 ; P ritchard 1986 ; L ightowlers and R ickard 1988 ; M aizels et al . 2018 ; A buzeid et al . 2020 ). ES proteins can be exported from cephalic/pharyngeal glands, intestine, or cuticle ( P ritchard 1986 ; Z han et al . 2003 ; H uang et al . 2020 ). Genes encoding ES proteins have been identified in the major human hookworm N. americanus ( L ogan et al . 2020 ), the dog hookworm Ancylostoma caninum ( M orante et al . 2017 ), and five strongylid parasitic nematodes closely related to hookworm: Angiostrongylus vasorum ( G illis -G ermitsch et al . 2021 ), Haemonchus contortus ( W ang et al . 2019 ), Heligmosomoides bakeri ( H ewitson et al . 2011 ; M oreno et al . 2011 ; H ewitson et al . 2013 ), Nippostrongylus brasiliensis ( S otillo et al . 2014 ), and Ostertagia ostertagi ( P rice et al . 2024 ) ( Figure 1 ). Until recently ( U zoechi et al . 2023 ), ES proteins have not been identified for the zoonotic human hookworm A. ceylanicum , which is an important zoonotic pathogen of humans and companion animals and which can complete its lifecycle in hamsters, making it a key hookworm species for laboratory studies ( G arside and B ehnke 1989 ; T raub 2013 ; S tracke et al . 2020 ; C olella et al . 2021 ). Download figure Open in new tab Figure 1. Morphology and evolution of the hookworm Ancylostoma ceylanicum . (A) Female of A. ceylanicum by 12 days after infection of a hamster host; scale bar, 500 μm. At this stage of development, the hookworms are young adults that have only just begun blood feeding, with mature males and a few gravid females, and with little or no egg laying. (B) Male of A. ceylanicum by 19 days after infection of a hamster host; scale bar, 1 mm. At this stage of development, the hookworms are fully mature adults that have been blood-feeding for at least a week, have mated, and have begun extensive egg laying that can last for weeks in a hamster host. Both photographs are reproduced from Schwarz et al . ( S chwarz et al . 2015 ). (C) Evolutionary relationships of the hookworm A. ceylanicum to some other nematodes discussed in this paper. This phylogeny links A. ceylanicum to other Ancylostoma and Necator hookworms, to more distantly related strongylid parasitic nematodes, and to two well-studied free-living rhabditid nematodes ( C. elegans and Pristionchus pacificus ). Phylogenetic data are taken from Coghlan et al ., van Megen et al ., and Xie et al . ( van M egen et al . 2009 ; X ie et al . 2017 ; C oghlan et al . 2019 ). A. ceylanicum is highlighted in gold; three parasitic species ( A. caninum , N. americanus , and H. contortus ) whose ES genes were compared to those of A. ceylanicum in this paper are highlighted in red. Hookworms form a single clade (marked with a yellow bar); they are a subset of a larger clade of strongylid nematodes (marked with a green bar) which, like hookworms, are parasitic. Strongylids are, in turn, a subset of rhabditid nematodes (marked with a blue bar); this clade encompasses both parasitic nematodes and the free-living nematodes C. elegans and P. pacificus . Notably, A. ceylanicum and other strongylid parasites are more closely related to C. elegans than to P. pacificus despite having highly divergent parasitic life cycles. To find A. ceylanicum genes whose products may enable parasitism, we have identified A. ceylanicum ES proteins, while also using RNA-seq to identify A. ceylanicum genes whose products interact with the host either through intestinally-biased expression or through upregulation in response to a functioning host immune system. For the latter set of genes, we hypothesized that the parasite transcriptionally activates genes in response to the host immune system in order to neutralize the host immune response. Previously, we found that changes of A. ceylanicum gene activity during infection in vivo are much more extensive than changes seen during simulated infection in vitro ( S chwarz et al . 2015 ). Here we build on that observation by correlating ES genes with intestinal and immunoregulated genes. We identify genes encoding immunoregulated intestinal ES proteins that may be important for virulence or immunosuppression, that are new targets for drugs or vaccines against hookworm, and that may aid in the development of therapies against autoimmune diseases. Methods Sample procurement, preparation and storage Cultures, infections, and collections of A. ceylanicum followed published methods ( H u et al . 2012 ; S chwarz et al . 2015 ). For each A. ceylanicum infection in support of RNA-seq, we purchased Syrian golden hamsters ( Mesocricetus auratus ) of the HsdHan:AURA strain at 3-4 weeks of age. Hamsters were provided with food and water ad libitum . For immunosuppression experiments, we immunosuppressed half of each set of hamsters by injecting them with dexamethasone (3 mg/kg) twice per week throughout the duration of the experiment ( T ritten et al . 2012 ); the other half were given mock injections. After the first two injections (one week), both immunocompetent and immunocompromised hamsters were infected at approximately four to five weeks of age with A. ceylanicum . Infections were allowed to progress for 12 or 19 days, after which we euthanized the hamsters and collected hookworms from small intestines dissected from the hamsters. Dissected hamster intestines were put into Hank’s Balanced Salt Solution (pre-warmed to 37°C); worms were picked quickly from the dissected tissues by hand. Collected worms were snap-frozen in liquid nitrogen and stored at −80°C until use. For A. ceylanicum infections in support of ES protein mass spectrometry, we followed a similar protocol but without injections, with two collections of A. ceylanicum at 20 days after infection, and without snap-freezing of dissected hookworms. Stages of A. ceylanicum selected for RNA-seq or proteomics are based on previously described stages of growth in golden hamsters ( R ay et al . 1972 ). For hookworm intestinal-specific studies, from each triplicate set of 19-day post-infection hookworms isolated from hamsters as above, we dissected both hookworm intestinal and hookworm non-intestinal tissue, and extracted RNA from the dissected tissues; for the triplicates of smaller 12-day post-infection young adult worms, such dissection was not possible, so we extracted RNA from whole 12-day young adult worms. All animal experiments were carried out under protocols approved by the University of Massachusetts Chan Medical School. All housing and care of laboratory animals used in this study conformed to the NIH Guide for the Care and Use of Laboratory Animals in Research (18-F22) and all requirements and all regulations issued by the USDA, including regulations implementing the Animal Welfare Act (P.L. 89-544) as amended (18-F23). RNA harvesting and sequencing Total A. ceylanicum RNA was extracted from either whole worms or from dissected tissues as in Romeo and Lemaitre ( R omeo and L emaitre 2008 ; S chwarz et al . 2015 ). RNA-seq was done largely as in Srinavasan et al . ( S rinivasan et al . 2013 ). RNA-seq libraries were built with Illumina’s TruSeq RNA Sample Prep Kit v2 executed according to manufacturer’s instructions, using 1 µg of total RNA for each sample. RNA-seq libraries were sequenced in single-end mode with read lengths of 50 nt (for all 19-day data) or 100 nt (for all 12-day data). Newly generated A. ceylanicum RNA-seq libraries are listed in Supplementary Table S1. Protein harvesting After 20 days of infection, A. ceylanicum hookworms were isolated from their hamster hosts and cultured in liquid culture medium for up to 3 days at 37°C in 5% CO 2 . Liquid culture medium consisted of RPMI Medium 1640 (Gibco, Cat#11835-030) supplemented with 25 mM pH 7.2 HEPES buffer, 10 µg/ml amphotericin B (Gibco, Cat# 15290-026), and 100 U/ml penicillin/streptomycin (Gibco, Cat# 1570-063), with medium sterilized with a 0.22 µm filter. Fetal bovine serum was omitted from the medium to eliminate any added protein when quantifying ES proteins by BCA assay and to eliminate contamination for proteomics. After the first 24 hours, proteins excreted or secreted from the hookworms were collected by aspirating media only. The aspirated media were centrifuged to remove debris (1500 gs for 20 minutes, at 4°C); the resulting supernatant was concentrated 10-fold using a 3kD Amicon ultra-centrifugal filter (4000 gs for 45 minutes, at 4°C). After this first 10-fold concentration, PBS was added to match the initial volume, after which the media were reconcentrated by again being centrifuged (4000 gs for 45 minutes, at 4°C); we repeated this twice, for a total of three PBS rinses and reconcentrations. After the third PBS rinse/reconcentration, total protein was quantified using a Pierce BCA Protein Assay kit. Purified ES proteins were then frozen and stored at −80°C. General computation Where possible, we used mamba to install and run version-controlled software environments from bioconda ( G runing et al . 2018 ). For reformatting or parsing of computational results, we used Perl scripts either developed for general use or custom-coded for a given analysis. All such Perl scripts (named below with italics and the suffix “ .pl ”) were archived on GitHub ( https://github.com/schwarzem/ems_perl ). Internet sources (URLs) for other software are listed in Supplementary Table S2. Nematode genomes, transcriptomes, coding sequences, and proteomes For transcriptomic or proteomic analyses, published genome sequences, coding sequences, proteomes, and gene annotations of relevant nematodes were downloaded from WormBase ( D avis et al . 2022 ) or ParaSite ( H owe et al . 2017 ; L ee et al . 2017 ) (Supplementary Table S3). Published RNA-seq data of A. ceylanicum ( S chwarz et al . 2015 ; W ei et al . 2016 ; B ernot et al . 2020 ) and H. contortus ( L aing et al . 2013 ) were downloaded from the European Nucleotide Archive (Supplementary Table S4). Alternative gene predictions for A. ceylanicum recently published by Uzoechi et al . ( U zoechi et al . 2023 ) were obtained as a Generic Feature Format Version 3 (GFF3) annotation file ( https://github.com/The-Sequence-Ontology/Specifications/blob/master/gff3.md ) from Young-Jun Choi that we have archived at https://osf.io/dxfsb . We extracted protein sequences from this GFF3 via gffread 0.12.7 ( P ertea and P ertea 2020 ) with the arguments ‘ -g [input genome sequence FASTA file] -o /dev/null -C --sort-alpha -- keep-genes -P -V -H -l 93 -y [output protein FASTA file] [input gene prediction GFF3 file] ’. Heligmosomoides species nomenclature . Recent genomic analysis has shown that the gastrointestinal parasitic nematode Heligmosomoides has two distinct species: H. bakeri and H. polygyrus ( S tevens et al . 2023 ). Although laboratory strains of Heligmosomoides have often been described as H. polygyrus ( M aizels et al . 2011 ), it now appears likely that many or all of these strains have actually been H. bakeri . Thus, following previous suggestions for revised nomenclature ( B ehnke and H arris 2010 ), we refer exclusively to H. bakeri even when citing published work that was nominally done with H. polygyrus . RNA-seq subsampling We found that published A. ceylanicum RNA-seq data (Supplementary Table S4) were too extensive for gene predictions by BRAKER2 because of memory limitations. To make these data usable by BRAKER2, we selected a representative subset of them with khmer ( Z hang et al . 2014 ; C rusoe et al . 2015 ). Because khmer requires “#/1” and “#/2” suffixes for paired-end reads, we retrofitted paired-end RNA-seq reads lacking such suffixes with retroname_fastq_reads.pl . We ran normalize-by-median.py from khmer on all data (paired and unpaired) twice, with the arguments ’-k 31 -C 100 -M 100G ’, and ’-k 31 -C 30 -M 100G ’; we then ran filter-abund.py from khmer on paired-end data with the arguments ‘ --variable-coverage -C 2 [k-mer hash] [paired-end reads] ’. We sorted khmer-filtered data into interleaved paired- and unpaired-end read files with paired_vs_unp_fastq.or.a.pl with the arguments ‘ --r1 “#0\/1” --r2 “#0\/2“ ’. Reprediction of protein-coding genes To repredict protein-coding genes in A. ceylanicum , we ran braker.pl in BRAKER2 2.1.6 ( B rŮna et al . 2021 ) on our published repeat-softmasked A. ceylanicum genome assembly ( S chwarz et al . 2015 ), with the arguments ‘ --genome [genome assembly FASTA] -- prot_seq [collected proteomes FASTA] --bam [sorted mapped khmer-filtered paired-end read BAM alignment] --etpmode --softmasking --cores 48 --gff3 ’. BRAKER2 requires an input genome sequence to have its FASTA header lines previously stripped of comments; we did this with uncomment_FASTA_headers.pl . Running BRAKER2 also required us to install: AUGUSTUS 3.4.0 ( S tanke et al . 2008 ); BamTools 2.5.2 ( B arnett et al . 2011 ); cdbfasta 0.99 ( P ertea et al . 2003 ); DIAMOND 2.0.9 ( B uchfink et al . 2021 ); GeneMark-ES/ET 4.68 ( L omsadze et al . 2014 ); and SAMtools 1.12 ( D anecek et al . 2021 ). To guide BRAKER2 gene predictions, we used our khmer-subsampled paired-end subset of published A. ceylanicum RNA-seq data, along with predicted proteomes from the related nematodes Caenorhabditis elegans ( D avis et al . 2022 ), H. contortus ( D oyle et al . 2020 ), and N. americanus ( L ogan et al . 2020 ). After running BRAKER2, we renamed gene, transcript, and exon names in the GFF3 prediction file with a modified version of updateBRAKERGff.py ( https://github.com/Gaius-Augustus/BRAKER/issues/416 ) and Perl one-line commands. To extract coding DNAs (CDS DNAs) and protein sequences from the renamed GFF3, we used gffread 0.12.7 ( P ertea and P ertea 2020 ) as above, with the additional argument ‘ -x [output CDS DNA file] ’. This gave us a new gene set (“v2.0”) that was generally superior (in completeness as assayed by BUSCO, and nonfragmentation as assayed by count_fasta_residues.pl ) to our original 2015 gene set (“v1.0”). However, we observed that some v1.0 genes encoded ES proteins (as determined by mass spectrophotometric mapping) but had no genomic overlap with v2.0 genes. To ensure no valid ES genes would be overlooked, we used BEDtools 2.30.0 ( Q uinlan and H all 2010 ) to identify v1.0 genes whose protein-coding exon sequences (CDSes) had no genomic overlap with v2.0 CDSes, as follows. We used get_gff3_gene_subset.pl to remove GFF3 v2.0 annotations that could not be translated by gffread, and then used Perl to extract CDS annotation lines from the GFF3 files of published v1.0 and gffread-translatable v2.0 gene predictions. We reformatted the CDS-subset files from GFF3 to BED with gff2bed in BEDOPS 2.4.41 ( N eph et al . 2012 ). We identified overlapping coordinates of the CDS-only BED annotation files for v1.0 and v2.0 genes with intersect from BEDtools 2.30.0 ( Q uinlan and H all 2010 ), using the argument ‘ -loj ’, and used Perl to extract a list of v1.0 genes having no CDS overlaps with v2.0 genes. Given this list of non-overlapping v1.0 genes, we used extract_fasta_subset.pl to extract their encoded CDS DNAs and proteins as subsets from the full published v1.0 CDS DNA and protein sets, and added these CDS DNA and protein subsets to our previous generated v2.0 CDS DNA and protein sequences. This gave us our final hybrid prediction set (“v2.1”) of CDS DNAs and proteins on which all further analyses in this paper were performed. The v2.1 CDS DNAs and proteome have been archived at https://osf.io/dxfsb . We generated a v2.1 GFF3 as follows. From the published v1.0 GFF3, we extracted GFF3 annotations for these non-overlapping v1.0 genes first by running extract_parasite_GFF3_subset.pl and then by selecting ‘ WormBase_imported ’ annotation lines with Perl. We reformatted the resulting v1.0 non-overlapping GFF3 with AGAT 1.1.0 ( D ainat 2023 ). Likewise, we reformatted the gffread-translatable v2.0 GFF3 with AGAT. We then merged the two AGAT-reformatted GFF3s to produce a single v2.1 GFF3 with uniform formatting, which we have archived at https://osf.io/dxfsb . Assessing quality of protein-coding genes We determined general statistics of protein-coding gene products with count_fasta_residues.pl using the arguments ‘ -e -t prot ’; we obtained gene counts from maximum-isoform proteome subsets generated with get_largest_isoforms.pl using the arguments ‘ -t parasite ’ or ’-t maker ’. We determined and compared the completeness of predicted A. ceylanicum protein-coding gene sets with BUSCO 5.2.2 using the arguments ‘ --lineage_dataset nematoda_odb10 --mode proteins ’ ( W aterhouse et al . 2018 ), which tested a given proteome against 3,131 highly conserved single-gene orthologs in nematodes. Gene reannotation For the protein products of our v2.1 A. ceylanicum gene set, we predicted both N-terminal signal sequences and transmembrane alpha-helical anchors with Phobius 1.01 ( K Äll et al . 2004 ), reformatting results with tabulate_phobius_hits.pl . We predicted coiled-coil domains with Ncoils 2002.08.22 ( L upas 1996 ), reformatting results with tabulate_ncoils_x.fa.pl . We predicted low-complexity regions with PSEG 1999.06.10 ( W ootton 1994 ) using the argument ‘ -l ’ and reformatting results with summarize_psegs.pl . We identified protein domains with Pfam 35.0 ( M istry et al . 2021 ) database with hmmscan in HMMER 3.3.2 ( E ddy 2009 ; F inn et al . 2016 ), using the arguments ‘ --cut_ga ’ to impose family-specific significance thresholds, ‘ -o /dev/null ’ to discard text outputs, and ‘ --tblout ’ to export tabular outputs; Pfam results were reformatted with pfam_hmmscan2annot.pl . We also identified protein domains with interproscan.sh in InterProScan 5.57-90.0 ( P aysan -L afosse et al . 2023 ) using the arguments ‘ -dp -iprlookup -goterms ’, and reformatting results with tabulate_iprscan_tsv.pl . We generated Gene Ontology (GO) terms ( A shburner et al . 2000 ; C arbon et al . 2021 ), EggNOG descriptions ( H ernandez -P laza et al . 2023 ), and KEGG codes ( K anehisa et al . 2023 ) with EnTAP 0.10.7-beta ( H art et al . 2020 ) using the argument ‘ --runP ’, and using selected UniProt ( U ni P rot 2023 ) and RefSeq ( O’L eary et al . 2016 ) proteome databases from highly GO-annotated model organisms (Supplementary Table S3); proteome databases were generated with makedb from DIAMOND 0.9.9 ( B uchfink et al . 2021 ), itself bundled with EnTAP; annotations from EnTAP were reformatted from protein to gene annotation tables with cds2gene_EnTAP_annot.pl and cds2gene_annot.pl . We identified genes encoding possible antimicrobial peptides (AMP) by mapping predictions by Irvine et al . ( I rvine et al . 2023 ) from v1.0 to v2.1 of our gene predictions. We identified orthologies between A. ceylanicum and other nematodes with OrthoFinder 2.5.4 ( E mms and K elly 2019 ) using the arguments ‘ -S diamond_ultra_sens -og ’; results were reformatted with prot2gene_ofind.pl and genes2omcls.pl . For all analyses except OrthoFinder, full proteomes were used; for OrthoFinder, we used maximum-isoform proteome subsets generated with get_largest_isoforms.pl . An overall annotation table was constructed from both these and RNA-seq annotations (below) with add_tab_annots.pl . Gene annotation for related parasitic nematodes To make consistent comparisons of ES genes (or other categories of genes) between A. ceylanicum and other species, we annotated the protein-coding genes for three related parasites ( A. caninum , H. contortus , and N. americanus ) using the same methods as for A. ceylanicum above; the analyzed proteomes are listed in Supplementary Table S3. Selection of ES gene sets from related parasitic nematodes for comparative analysis We selected three published ES gene sets from A. caninum , H. contortus , and N. americanus for comparative analysis by the following criteria. They had to have either gene identification numbers (IDs) from public genome assemblies, or, if they did not have gene IDs from valid genomes, they needed to at least have expressed sequence tag (EST) IDs for which the original sequence data were publicly available so that they could be mapped onto genomes (and thus to modern genes with proper IDs). This requirement disqualified previously published ES gene sets for H. bakeri and N. brasiliensis . Second, the gene IDs needed to be correctly mapped from protein mass spectrometric data of one species onto genes of the same species. Remarkably, this requirement disqualified the ES genes from Angiostrongylus , which were generated from A. vasorum protein mass spectrometry data but were mapped onto genes of A. cantonensis and A. costaricensis . Third, the ES genes needed to be from parasitic nematodes that had evolved parasitism in common with A. ceylanicum hookworms. This criterion disqualified ES genes from the giant roundworm Ascaris suum or the whipworm Trichuris muris , which evolved parasitism independently of hookworms and other strongylids. RNA-seq data For A. ceylanicum , we generated biologically triplicated RNA-seq data for each biological condition. We also analyzed published RNA-seq data for A. ceylanicum ( S chwarz et al . 2015 ; W ei et al . 2016 ; B ernot et al . 2020 ) and H. contortus ( L aing et al . 2013 ), listed in Supplementary Table S4. Before analysis, we Chastity-filtered new A. ceylanicum RNA-seq reads with quality_trim_fastq.pl using the arguments ’-q 33 -m 50’ . We then quality-filtered and adaptor-trimmed new A. ceylanicum RNA-seq reads with fastp 0.20.0 ( C hen et al . 2018 ) using the arguments ‘-- dont_overwrite --detect_adapter_for_pe --n_base_limit 0 --length_required X ’, with X = 50 for new A. ceylanicum data. We quality-filtered and adaptor-trimmed previously published A. ceylanicum and H. contortus RNA-seq reads with fastp 0.20.0 using the arguments ‘ --dont_overwrite --n_base_limit 0 --length_required X ’ with X = 50 for A. ceylanicum . RNA-seq expression values and significances We quantified gene expression from RNA-seq data sets with Salmon 1.9.0, generating expression values in transcripts per million (TPM) and estimating mapped read counts per gene ( P atro et al . 2017 ). To prevent spurious mappings of RNA-seq reads, we used full selective alignment to a “gentrome” (a CDS DNA set, treated as a target for real mappings, combined with its genome, treated as a decoy for spurious mappings), followed by quantification using Salmon in non-alignment mode ( S rivastava et al . 2020 ; S rivastava et al . 2021 ). For Salmon’s index program, we used the arguments ‘ --no-version-check --keepDuplicates -t [gentrome sequence] -d [decoy list]’; for Salmon’s quant program, we used the arguments ‘ --no-version-check --seqBias --gcBias -- posBias --libType A --geneMap [transcript-to-gene table]’, with ‘ --unmatedReads ’ used for single-end data. Results from quant.genes.sf output files were reformatted with make_salmon_TPM_slices.pl . Heatmapping of RNA-seq data To visualize and cluster gene expression values for RNA-seq replicates, we converted expression values of 0 TPM to empirical pseudozeros with assort_tpms.pl , with each replicate’s empirical pseudozero being defined as the lowest non-zero TPM expression value observed for all genes within that replicate. This allowed logarithmic transformation of zero expression values while defining these values in a replicate-specific way. We then converted the expression values of replicates to log 10 (TPM) scores with log10_tsv_numbers.pl . Finally, we heatmapped and dendrogram-clustered all replicates with ComplexHeatmap 2.18.0 ( G u 2022 ) using default parameters. Heatmapping showed individual non-dexamethasone (nonDEX) and dexamethasone (DEX) intestinal RNA-seq replicates that anomalously clustered with two DEX and nonDEX intestinal RNA-seq replicates, respectively ( Supplementary Figure 1 ); these anomalous replicates were thus not used for differential gene expression analysis. Differential gene expression analysis Having generated RNA-seq readcounts, we used the exactTest function of edgeR 3.36.0 ( R obinson et al . 2010 ) to compute log 2 fold-changes (log2FC) and false discovery rate (FDR) significance values ( N oble 2009 ), to identify statistically significant changes of gene expression between pairs of biological conditions in our RNA-seq data. Dispersions were computed with edgeR’s estimateDisp function using the argument ‘ robust=TRUE ’. For this analysis, we used all non-anomalous replicates of our A. ceylanicum RNA-seq data (Supplementary Table S1) along with published A. ceylanicum RNA-seq data from whole fourth-stage larval (L4) males, whole adult males, whole adult females, and adult male intestine (Supplementary Table S4). To increase the statistical signal for differentially expressed genes, we used filter_minimum_readcounts.pl with the argument ‘ 10 ’ to remove genes which failed to achieve 10 mapped reads in any biological replicate before submitting readcounts to edgeR. An edgeR R script (Supplementary File S1) was generated with make_edgeR_classic_scripts.pl , and run in batch mode with R 4.1.3. In summarizing edgeR results, we defined a gene as being differentially expressed (e.g., with tissue-, sex-, or condition-biased expression) if edgeR scored it as being ≥2-fold more strongly or weakly expressed in one condition than another (either log2FC ≥ 1, or log2FC ≤ −1) with an FDR of ≤ 0.01. All other genes with intermediate expression ratios between two conditions (−1 < log2FC 0.01) were not classified as having differential gene expression. We used edgeR’s exactTest with these criteria because it is well-adapted for analyzing small numbers of biological replicates ( S church et al . 2016 ). RNA-seq and differential gene expression analysis for H. contortus These were performed with published RNA-seq data for dissected adult female intestine and whole adult female bodies (Supplementary Table S4) ( L aing et al . 2013 ) and with predicted genes from the published chromosomal reference genome (Supplementary Table S3) ( D oyle et al . 2020 ), by the same methods as used for A. ceylanicum . Constructing a protein set for mass spectrophotometric analysis To combine our newly predicted A. ceylanicum proteins with alternative predictions by Coghlan et al . ( C oghlan et al . 2019 ), we ran cd-hit-2d from CD-HIT 4.8.1 ( L i and G odzik 2006 ) with the arguments ‘ -i [v2.1 predicted proteome] -i2 [alternative published proteome by Coghlan et al.] -o [distinct Coghlan protein sequences] -d 100 -c 1.0 -M 0 -T 1 -l 5 -s 0.0 -aL 0.0 -aS 1.0 ’. We then joined the v2.1 proteome with distinct Coghlan sequences to yield a nonredundant A. ceylanicum protein set for LC-MS/MS analysis. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis Peptides were analyzed with an Orbitrap Exploris 480 hybrid quadrupole-Orbitrap mass spectrometer coupled to an UltiMate 3000 RSLCnano liquid chromatography system (ThermoFisher Scientific). Peptides were loaded onto an Acclaim PepMap RSLC column (75 µm × 15 cm, 2 µm particle size, 100 Å pore size, ThermoFisher Scientific) over 15 min in 97% mobile phase A (0.1% formic acid) and 3% mobile phase B (0.1% formic acid, 80% acetonitrile) at 0.5 µL/min. Peptides were eluted at 0.3 µL/min using a linear gradient from 3% mobile phase B to 50% mobile phase B over 120 min. Peptides were electrosprayed through a nanospray emitter tip connected to the column by applying 2000 V through the ion source’s DirectJunction adapter. Full MS scans were performed at a resolution of 60,000 at 200 m/z over a range of 300-1,200 m/z with an AGC target of 300% and the maximum injection time set to ‘auto’. The top 20 most abundant precursors with a charge state of 2-6 were selected for MS/MS analysis with an isolation window of 1.4 m/z and a precursor intensity threshold of 5 × 103. A dynamic exclusion window of 20 s with a precursor mass tolerance of ± 10 ppm was used. MS/MS scans were performed using HCD fragmentation using a normalized collision energy of 30% and a resolution of 15,000 with a fixed first mass of 110 m/z. The AGC target was set to ‘standard’ with a maximum injection time of 22 ms. Mass spectrometry data analysis Thermo RAW files were searched against our nonredundant A. ceylanicum protein set using the SEQUEST algorithm in Proteome Discoverer 2.4 (Thermo). Data were searched for peptides with tryptic specificity with a maximum of two missed cleavages. The precursor mass tolerance was set at 10 ppm and the fragment mass tolerance was set at 0.02 Da. Search parameters included carbamidomethylation at cysteine (+57.021 Da) as a constant modification and the following dynamic modifications: oxidation at Met (+15.995 Da), acetylation at protein N-termini (+42.011 Da), Met loss at protein N-termini (−131.040 Da), Met loss+acetylation at protein N-termini (−89.030 Da). The Percolator node of Proteome Discoverer was used for PSM validation at a false discovery rate of 1%. Final results for both LC-MS/MS analyses are given in Supplementary Table S5. Mapping ES mass spectrometry hits onto our gene predictions Our protein database for analyzing ES data included both our new v2.1 A. ceylanicum predictions and any predictions by Coghlan et al . that differed by even one amino acid residue from ours. We selected ES protein hits in Supplementary Table S5 whose experimental combined q-value was ≤0.01; for each ES sample, we extracted their gene names as separate v2.1 and Coghlan genes, yielding four ES gene lists in all. Because gene prediction in complex eukaryotes remains challenging ( H atje et al . 2019 ) and because the Coghlan predictions were made on a different strain of A. ceylanicum (Indian strain, US National Parasite Collection Number 102954) than our laboratory strain used for genome sequencing and gene prediction (HY135), ES proteins whose mass spectrophotometic data fit a Coghlan prediction exclusively might do so only through slight differences in predicted gene structures or through strain-specific amino acid polymorphisms. To identify such cases where a Coghlan gene was equivalent to one of our v2.1 genes, we mapped the protein-coding exons (CDSes) of Coghlan genes onto our v2.1 gene set, as follows. We downloaded Coghlan gene annotations in GFF3 format and their corresponding A. ceylanicum genome assembly from ParaSite (Supplementary Table S3). We mapped the coordinates of Coghlan gene annotations onto our A. ceylanicum genome assembly sequence (i.e., lifted them over) with Liftoff 1.6.3 ( S humate and S alzberg 2020 ) using the arguments ‘ -copies -polish -cds ’. We extracted CDS coordinate lines from the resulting liftover GFF3 file with Perl, and did likewise for the CDS coordinates from the GFF3 of our v2.1 gene prediction set. We converted Coghlan and v2.1 CDS coordinate files from GFF3 to BED format with gff2bed in BEDOPS 2.4.41 ( N eph et al . 2012 ). We identified overlapping Coghlan and v2.1 CDSes with intersect in BEDtools 2.30.0 ( Q uinlan and H all 2010 ), using the argument ‘ -loj ’. We extracted columns 10 and 20 from the resulting intersection file with cut ( https://www.gnu.org/software/coreutils/cut ) using the argument ‘ -f 10,20 ’, and processed the results with washu.cds_loj_umass.cds_genemap.pl using the positional arguments ‘ [CDS-to-gene table] [BEDtools intersect columns 10 and 20 table] ’; the CDS-to-gene map file was extracted from the FASTA headers of Coghlan and v2.1 proteomes via Perl. We then used annot_es_v01.pl with our Coghlan-to-v2.1 gene map and our four ES gene lists to produce a unified list of ES-encoding v2.1 genes. Mapping ES genes of Uzoechi et al. onto our gene predictions Uzoechi et al . have recently identified ES-encoding genes in A. ceylanicum , using their own reprediction of our original 2015 gene set ( U zoechi et al . 2023 ). To compare their results to ours, we first mapped their results from ES transcripts to ES genes with map_tx_to_genes.pl . We then mapped their predicted gene set onto ours using methods similar to those for the Coghlan gene set. Because their repredictions were performed on our A. ceylanicum HY135 genome sequence rather than their A. ceylanicum Indian genome (as Coghlan predictions had been), we did not need to use Liftoff to map coordinates from one genome to the other. Subsequent mapping steps (CDS extraction with Perl; GFF to BED conversion with BEDOPS gff2bed ; overlap determination with BEDtools intersect ; extraction and summarizing of ES gene results with annot_es_v02.pl ) were as above. Statistical significance of overlapping gene sets To identify significant overlaps between sets of A. ceylanicum genes, we used the Perl script motif_group_fisher.pl , which computed p-values from two-tailed Fisher tests with the Perl module Text::NSP::Measures::2D::Fisher::twotailed ; for multiple hypothesis testing (e.g., comparisons to sets of protein motifs) this Perl script also computed q-values via the qvalue program of the MEME 5.4.1 software suite ( B ailey et al . 2009 ). Results Improved A. ceylanicum gene predictions Analyzing gene function depends crucially on the quality of gene predictions ( H atje et al . 2019 ; G uigÓ 2023 ). Our published gene set for A. ceylanicum (“version 1.0” or “v1.0“; Table 1 ) used the best resources we had at the time ( S chwarz et al . 2015 ), but both software and RNA-seq/protein data for gene prediction have improved since 2015. We thus repredicted A. ceylanicum protein-coding genes with BRAKER2 ( B rŮna et al . 2021 ), whose predictions we guided with both greatly expanded RNA-seq data sets across the A. ceylanicum life cycle ( S chwarz et al . 2015 ; W ei et al . 2016 ; B ernot et al . 2020 ) and protein sequences from related nematodes ( D oyle et al . 2020 ; L ogan et al . 2020 ; D avis et al . 2022 ). We assessed our gene predictions and compared them to others with BUSCO ( W aterhouse et al . 2018 ), checking for the presence of 3,131 highly conserved single-copy index genes in nematodes and defining completeness by the percentage of index genes found in a given gene set ( Table 1 ). This gave us an initial repredicted gene set (“version 2.0” or “v2.0”) that was more complete and less fragmented than previous A. ceylanicum gene predictions by either us or others. Whereas our v1.0 predictions had detected 87.8% of BUSCO index genes, our v2.0 predictions detected 95.1%. The v2.0 set also had fewer protein-coding genes than v1.0 (19,419 versus 36,687) encoding longer proteins (medians of 300 versus 199 residues), implying that gene predictions in v2.0 were less fragmented than in v1.0. However, we observed that v1.0 included genes that encoded ES proteins (see below) yet were absent from the v2.0 gene set. To detect as many valid ES genes as possible, we identified all v1.0 genes whose exons were completely nonoverlapping with exons of v2.0 genes, and combined them with v2.0 to make a hybrid v2.1 set of 33,190 protein-coding genes. This v2.1 set showed a small but detectable increase in BUSCO completeness over v2.0 (95.1% to 95.3%). Recently, Uzoechi et al . have also repredicted A. ceylanicum genes using methods similar to ours ( U zoechi et al . 2023 ); their new gene set is also substantially better than earlier predictions (94.5% completeness), though less complete than our v2.0 or v2.1 gene sets ( Table 1 ). Having predicted the v2.1 gene set, we annotated its predicted protein products with predicted N-terminal signal sequences ( K Äll et al . 2004 ), conserved protein domains ( M istry et al . 2021 ; P aysan -L afosse et al . 2023 ), orthologies to genes in related nematode species such as N. americanus ( E mms and K elly 2019 ), and Gene Ontology (GO) terms describing biological and molecular functions ( A shburner et al . 2000 ; C arbon et al . 2021 ); annotations are listed in Supplementary Table S6. View this table: View inline View popup Download powerpoint Table 1. Protein-coding gene predictions for A. ceylanicum . Identifying ES proteins To collect ES proteins from adult A. ceylanicum hookworms, we isolated hookworms from hamster hosts 20 days after infection in two independent experiments, incubated the hookworms in protein-free culture medium for three days, concentrated and purified their supernatants, subjected their proteins to mass spectrometry, and mapped the resulting protein spectra to a nonredundant set of protein sequences. By this means, we identified 565 genes encoding ES proteins observed in at least one ES collection (1.7% of all genes), and 350 genes encoding ES proteins in both independent collections (1.05% of all genes; Table 2 ; Supplementary Table S6). Uzoechi et al . have also identified genes encoding ES proteins from male and female A. ceylanicum ( U zoechi et al . 2023 ); mapping their ES genes onto our v2.1 gene set, we find 860 ES genes from their analysis (2.6% of all genes), of which 430 are identical to ES genes from ours (1.3% of all genes; 76% of our ES genes). This overlap is 29-fold greater than chance (two-tailed Fisher test, p-value = 0), and shows high reproduciblity of ES genes in A. ceylanicum . Conversely, each ES gene set has unique members; they collectively have 995 genes ( Table 2 ). View this table: View inline View popup Download powerpoint Table 2. Numbers of genes encoding ES proteins of A. ceylanicum . Out of our 565 ES genes, we consider two subsets for detailed analysis here: either categories of ES genes for which we can show statistically significantly enhanced overlaps with other gene categories of interest, or individual instances of ES genes for which we have found specific published information in the literature which indicates that an individual ES gene may have a biologically informative function or effect. A. ceylanicum ES genes encode possible host-parasite interaction proteins Two-thirds of our ES genes (380) were predicted to encode classically secreted proteins with N-terminal signal sequences, 4.6-fold above genome-wide background (q = 4.5•10 −181 ); the remaining one-third of ES genes (185) encode proteins that are presumably non-classically secreted ( Table 3 ; Supplementary Table S7) ( D imou and N ickel 2018 ). This mix of predominant but not universal N-terminal signals also exists in ES proteins from A. caninum , N. americanus , and H. contortus (Supplementary Tables S8-S10) ( M orante et al . 2017 ; W ang et al . 2019 ; L ogan et al . 2020 ), and may reflect nonclassical secretion of ES proteins through extracellular vesicles ( B almer and F aso 2021 ; W ang et al . 2024 ). View this table: View inline View popup Download powerpoint Table 3. Protein motifs overrepresented in A. ceylanicum ES genes. Compared to the whole A. ceylanicum proteome, ES genes disproportionately encoded several protein families with plausible roles in host-parasite interactions ( Table 3 ; Supplementary Table S7) ( A buzeid et al . 2020 ). These included five types of proteases (aspartyl, astacin, cysteine, serine, and metallopeptidase) that may digest host tissues and blood ( W illiamson et al . 2006 ; R anjit et al . 2009 ; K nox 2012 ; Y ang et al . 2015 ; C affrey et al . 2018 ), along with three types of protease inhibitors (Kunitz, TIL, and TIMP) that may protect A. ceylanicum from native or host proteases; both proteases and protease inhibitors may also counteract host immune responses ( C hu et al . 2004 ; K nox 2007 ). Five ES genes encoded glutathione S-transferase, an enzyme thought to detoxify free heme generated during hemoglobin proteolysis and other toxins ( M atouskova et al . 2016 ; A buzeid et al . 2020 ). Sixteen ES genes encoded Stichodactyla helianthus toxin (ShK)-related proteins, which might suppress host T cells ( C hhabra et al . 2014 ; M c N eilly et al . 2017 ); and nine ES genes encoded C-type lectin proteins, which might mimic mammalian immune proteins (enabling immunosuppression) or dissociate cells (enabling tissue invasion) ( L oukas et al . 2000 ; H arcus et al . 2009 ; Y oshida et al . 2012 ; S chwarz et al . 2015 ; W ang et al . 2023 ). One quarter of ES genes (140) encoded secreted venom-like allergen proteins with CAP or SCP/TAPS domains ( G ibbs et al . 2008 ; C antacessi et al . 2009 ); in hookworms, these are called Ancylostoma secreted proteins, activation-associated secreted proteins, or ASPs ( H awdon et al . 1996 ; Y atsuda et al . 2002 ; W ilbers et al . 2018 ). One ASP, neutrophil inhibitory factor in A. caninum ( Acan -NIF), has been experimentally shown to block neutrophil adhesion ( M oyle et al . 1994 ; L o et al . 1999 ); another ASP, hookworm platelet inhibitor in A. caninum ( Acan -HPI), has been shown to prevent blood clotting ( D el V alle et al . 2003 ). We observed ES genes encoding orthologs of both these ASPs ( Acey -NIF-B and Acey -HPI) which may themselves be immunosuppressant and antithrombotic proteins (Supplementary Table S6). However, this leaves the other 138 ES ASP genes with only conjectural functions. ES genes also encode three other multigene families of secreted proteins that are suspected to be involved in infection, although their molecular roles remain largely uncharacterized: ASP-related (ASPR), transthyretin-like (TTL), and secreted clade V proteins (SCVP). ASPRs were first observed in A. ceylanicum as a divergent subfamily of ASPs transcriptionally upregulated immediately after host infection ( S chwarz et al . 2015 ), and were later observed in ES proteins from N. americanus ( L ogan et al . 2020 ). TTL proteins were previously observed as a major component of ES proteins from H. contortus ( W ang et al . 2019 ) and as multigene families in several parasitic nematodes ( H unt et al . 2017 ; T ritten et al . 2021 ; S tevens et al . 2023 ); one TTL protein of H. contortus ( Hc TTR) antagonizes goat IL-4 in vitro , and thus may be immunosuppressive in vivo ( T ian et al . 2019 ). SCVPs were observed in A. ceylanicum as a novel family of secreted proteins upregulated in young hookworm adults that is conserved in C. elegans and expanded in hookworms and other strongylids ( S chwarz et al . 2015 ). Other ES genes were potentially relevant to infection despite not being from overrepresented families ( Table 4 ). One encodes a macin homolog that may protect hookworms from being infected by bacteria, and thus enable their long-term residence in the human gut ( J ung et al . 2012 ; I rvine et al . 2023 ). Three ES homologs of A. caninum anticoagulant protein ( S tassens et al . 1996 ) could act with Acey -HPI to prevent clotting during blood feeding. Seven other ES genes encode possible immunosuppressants: two ES apyrases and one ES adenosine deaminase could suppress both blood clotting and inflammation by hydrolyzing extracellular ATP ( G ounaris and S elkirk 2005 ; G uiguet et al . 2016 ; P ala et al . 2023 ); phospholipase A2, phospolipase D, and fatty acid- and retinol-binding (FAR) ES proteins could suppress lipid signals in immune responses ( P arks et al . 2021 ; P arks et al . 2023 ); the ES macrophage migration inhibitory factor Acey -MIF-1, previously observed to bind the human MIF receptor CD74 and promote monocyte migration, could alter cellular immune responses ( C ho et al . 2007 ; S parkes et al . 2017 ); and an ES deoxyribonuclease II could hydrolyze extracellular DNA nets secreted by neutrophils to trap and kill large pathogens ( B ouchery et al . 2020 ). View this table: View inline View popup Download powerpoint Table 4. Individual A. ceylanicum ES genes of interest. Because ES proteins are exposed to the human host’s immune system and are likely to promote infection, ES proteins are promising targets for an anti-hookworm vaccine. Twelve ES genes encoded proteins that have already been shown to give partial protection as vaccines in laboratory mammals, or to be homologous to such proteins ( Table 4 ): the cysteine protease Acey -CP-1 ( N oon et al . 2019 ); the M13 peptidases Acey -MEP-6 and Acey -MEP-7 ( W isniewski et al . 2013 ; W isniewski et al . 2016 ); the glutathione S-transferase Acey -GST-1, homologous to A. caninum ’s Acan -GST-1 ( X iao et al . 2008 ) and N. americanus’ Na -GST-1 ( Z han et al . 2010 ); a homolog of the immunodominant hypodermal Ac -16 antigen of A. caninum ( F ujiwara et al . 2007 ); two homologs of apyrases in Teledorsagia circumcincta and H. bakeri ( N isbet et al . 2019 ; B erkachy et al . 2021 ); two homologs of fatty acid- and retinol-binding proteins in A. ceylanicum ( F airfax et al . 2009 ) and Onchocerca volvulus ( J enkins et al . 1996 ); one homolog of Brugia malayi calreticulin ( Y adav et al . 2021 ); one homolog of Onchocerca volvulus fructose-1,6-bisphosphate aldolase ( M c C arthy et al . 2002 ); and one homolog to A. suum enolase ( C hen et al . 2012 ). In addition to these strict orthologs, three instances of astacin, ASP, and TTL proteins (all overrepresented among ES proteins) have given partial protection as vaccines: Ac -MTP-1 of A. caninum , Acan -ASP-2 of A. caninum , and Hc TTR of H. contortus ( Z han et al . 2002 ; B ethony et al . 2005 ; T ian et al . 2020 ). These results show the vaccine potential of ES proteins, with hundreds of other ES proteins remaining untested as vaccine subunits. Over half of A. ceylanicum ES genes are functionally conserved in related blood-feeding parasitic nematodes: they do not merely have homologs, but ES gene homologs ( Table 5 ; Supplementary Tables S6 and S11). Out of 565 A. ceylanicum ES genes, 269 (47.6%) had ES gene homologs in the closely related hookworm A. caninum ( M orante et al . 2017 ), 21-fold more than expected by chance (p = 6.82•10 −301 ). For the more distantly related hookworm N. americanus ( L ogan et al . 2020 ), 141/565 ES genes (25.0%) had ES gene homologs (18-fold over chance; p = 1.78•10 −137 ); for the still more distantly related blood-feeding H. contortus ( W ang et al . 2019 ), 180/565 ES genes (31.9%) had ES gene homologs (8.9-fold over chance, p = 4.10•10 −120 ). Considering all three species at once, 350/565 ES genes (61.9%) had some ES homolog (12-fold over chance, p = 0). Similarly high conservation was observed for the 860 ES genes described by Uzoechi et al . (Supplementary Table S11) ( U zoechi et al . 2023 ). These homologies of A. ceylanicum ES genes in other species are predominantly to ES genes themselves (i.e., genes experimentally shown to encode ES proteins in these other species). When ES genes in other species are set aside, the remaining homologies of A. ceylanicum ES genes fall to, or even below, background frequencies. For A. ceylanicum ES genes without known ES gene homologs, homology to A. caninum dropped to 1.6-fold over chance (p = 1.31•10 −29 ); in N. americanus , to 1.1-fold below chance (p = 0.22); and in H. contortus , to 2.4-fold below chance (p = 2.05•10 −30 ). Thus, the A. ceylanicum ES gene set predominantly encodes ES proteins not only in A. ceylanicum itself but also in related parasitic nematodes. Identification of intestinal and immunoregulated genes Because the hookworm intestine is an important source of ES proteins, we set out to characterize intestine- and non-intestine-biased expression of hookworm genes. We infected hamsters with A. ceylanicum hookworms, allowed infections to proceed for either 12 or 19 days, collected hookworms from hamster small intestines, extracted hookworm RNAs, and performed RNA-seq with 36.9 to 55.8 million reads per biological replicate (Supplementary Table S1). Hookworms at the 12-day infection stage were young adults that were too small for us to dissect further, so RNA-seq was done on whole 12-day hookworms. By 19 days, hookworms had grown into mature adults large enough to dissect, so we separated them into intestinal and non-intestinal tissues before RNA-seq. In addition, we hypothesized that hookworms would respond to the mammalian host’s immune system by increasing their expression of proteins that counteract the mammalian immune system. To detect hookworm genes regulated by the state of the host’s immune system, 12-day and 19-day infections were performed both with normal hamster hosts (nonDEX) and with hamsters whose immune systems had been suppressed by dexamethasone (DEX). We analyzed levels and changes of gene expression both for our RNA-seq data and for published A. ceylanicum RNA-seq data from adult male intestine, male adults, and female adults ( Table 6 ; Figure 2 ; Supplementary Table S6). We defined a gene as significantly changing its activity between two biological conditions (e.g., intestinal versus non-intestinal 19-day tissues, or intestinal nonDEX versus intestinal DEX) if the gene changed its expression by at least 2-fold (log2FC ≤ −1 or ≥ 1) with a false discovery rate (p-value corrected for multiple hypothesis testing) of no more than 0.01 (FDR ≤ 0.01). View this table: View inline View popup Table 5. Homologies of ES genes of A. ceylanicum to those of related parasitic nematodes. View this table: View inline View popup Download powerpoint Table 6. Numbers of A. ceylanicum genes showing differential RNA expression (significant changes of gene expression between biological conditions). Download figure Open in new tab Figure 2. Gene expression in A. ceylanicum . Gene activity is shown for 8,130 A. ceylanicum genes with significant differences in expression between biological conditions, with biological replicates used for differential gene expression analysis on the x-axis and individual genes on the y-axis. Expression levels are in TPM (log10). Genes sharing similar patterns of expression are split into 10 clusters. Biological replicates are: young 12-day hookworm adults from normal hosts (YA_12dpi_noDEX); young 12-day adults from immunosuppressed hosts (YA_12dpi_DEX); dissected 19-day intestines from mature hookworm adults in normal hosts (intestines_19dpi_noDEX); dissected 19-day intestines in immunosuppressed hosts (intestines_19dpi_DEX); dissected 19-day intestines in normal hosts (non.intestines_19dpi_noDEX); dissected 19-day non-intestinal tissues in immunosuppressed hosts (non.intestines_19dpi_DEX); previously published adult male intestine (WashU_male_intestine); published adult males (WashU_adult_male); and published adult females (WashU_adult_fem). Additional heatmaps of gene expression for all 33,190 genes and all replicates are given in Supplemental Figure 1. By these criteria, in 19-day adults we observed 1,670 genes with intestine-biased expression and 1,196 with non-intestine-biased expression, the remaining 30,324 genes being intermediate ( Table 6 ; Figure 2 ). Of the intestine-biased genes, 723 (43.3%) were homologous to H. contortus genes with intestine-biased expression (4.4-fold above background; p = 8.18•10 −306 ; Supplemental Table S15). For comparison, when we reanalyzed published RNA-seq data for male intestine versus whole male adults ( W ei et al . 2016 ; B ernot et al . 2020 ) as part of the same computation, we identified 635 genes with intestine-biased expression, of which only 180 were also found in our intestine-biased gene set (Supplementary Table S13). By chance alone, one would expect to observe 32 genes shared by both intestinal sets; the observed overlap was 5.6-fold above background (p = 9.93•10 −85 ) but limited (only 28% of the 635 genes were shared). The observation of over 700 genes with intestine-biased expression conserved between strongylids supports our larger gene set. The disagreement of these intestine-biased gene sets could have one or more causes: different protocols for dissection and RNA extraction; different background tissues for comparison to intestinal RNA-seq (non-intestinal here, versus whole adults in the previous data); different sexes (mixed-sex here, versus males previously); and different strains of A. ceylanicum (HY135 here, versus Indian previously), which could cause different rates of RNA-seq read mapping onto our HY135 reference genome (Supplementary Table S12) ( D egner et al . 2009 ; R ezansoff et al . 2019 ; B ell et al . 2023 ). When comparing A. ceylanicum in normal (nonDEX) versus immunosuppressed (DEX) hosts, we detected substantial changes of gene expression in 19-day hookworm intestinal tissues, but almost no changes of gene expression either in 12-day young adults or in 19-day non-intestinal tissues. We observed 1,951 genes upregulated in 19-day nonDEX intestine versus 19-day DEX intestine (5.9% of all genes), along with 137 downregulated genes (0.41%). In contrast, we observed only 32 genes positively or negatively immunoregulated either in 12-day young adults or in 19-day non-intestinal tissues ( Table 6 ; Figure 2 ). One explanation for this pattern is that only 19-day intestinal tissues are directly exposed to the host’s immune system through blood feeding. Although 12-day young adult hookworms inhabit the small intestine, they have only just started feeding on blood; up to that point, they instead probably eat mucosal cells ( B ansemir and S ukhdeo 1994 ; B ansemir and S ukhdeo 2001 ). By 19 days, hookworm adults have been feeding on blood for up to a week; however, most of their bodily contact with this blood (and, thus, with the host’s immune system) is through the lumen of their intestine (although cephalic or pharyngeal glands may interact with their host as well). Intestine-biased genes encode likely components of food digestion, detoxification, and absorption Whereas ES genes overwhelmingly encoded proteins with N-terminal signal sequences alone, intestine-biased genes were modestly but significantly enriched for several predicted types of secreted or transmembrane proteins ( Table 7 ; Supplementary Table S13). These included secreted proteins, proteins predicted to have one transmembrane anchor sequence after the N-terminal signal peptide, and multi-transmembrane proteins. Intestinal genes disproportionately encoded protein families relevant to digesting, detoxifying, and absorbing food ( Table 7 ): aspartyl, cysteine, aminopeptidase, and metallopeptidase proteases ( W illiamson et al . 2006 ; R anjit et al . 2009 ; K nox 2012 ; Y ang et al . 2015 ; C affrey et al . 2018 ); UDP-glucoronosyl or UDP-glucosyl transferases, ecdysteroid kinase-like enzymes, and ABC transporters ( M atouskova et al . 2016 ; S canlan et al . 2022 ; R aza et al . 2023 ); and major facilitator and sugar transporters ( C hen et al . 2015 ; D rew et al . 2021 ). Intestinal genes also disproportionately encoded histones; this raises the question of whether mitosis persists in the adult hookworm intestine, as has been observed or inferred for A. suum and H. bakeri ( A nisimov and T okmakova 1974 ; A nisimov and U sheva 1974 ; P ollo et al . 2024 ). In addition to these well-studied protein families, another notably overrepresented family was Strongylid L4 proteins (SL4Ps), first observed in A. ceylanicum as a novel family of non-classically secreted proteins upregulated in fourth-stage (L4) larvae ( S chwarz et al . 2015 ). Analyzing previously published H. contortus intestinal RNA-seq data (Supplementary Table S4), we observed that SL4P genes were also disproportionately represented among intestine-biased H. contortus genes, along with several of the better-characterized protein families implicated in digestion, detoxification, or absorption (e.g., cysteine proteases, UDP-glucoronosyl/glucosyl transferases, and major facilitator transporters; Supplementary Table S14). Moreover, the C. elegans genes numr-1 and numr-2 encode SL4P proteins that are intestinally expressed ( T vermoes et al . 2010 ). We conclude that SL4Ps have conserved intestinal expression in hookworms and other nematodes, and that (as in C. elegans ) their function might be to counteract toxic environmental stresses ( W u et al . 2019 ; H ong et al . 2024 ). View this table: View inline View popup Download powerpoint Table 7. Protein motifs overrepresented in A. ceylanicum genes with intestine-biased expression. Immunoregulated genes encode signal transduction, male-associated, host-parasite, and ES proteins The 1,951 positively immunoregulated intestinal genes were modestly, but significantly, enriched for encoding secreted proteins, proteins with a single transmembrane anchor, or both: in other words, possible secreted or cell-surface proteins ( Table 8 ). Overrepresented protein families included possible signal transduction components: protein kinases, protein phosphatases, and SH2 scaffold proteins ( T aylor and K ornev 2011 ; D iop et al . 2022 ; K okot and K ohn 2022 ). Other overrepresented families included homologs of nematode motile sperm proteins (MSPs) ( S mith 2014 ), along with two other classes of proteins associated with MSPs: MSP fiber 2 proteins (MFP2s) ( G rant et al . 2005 ) and DUF236 proteins ( R Ödelsperger et al . 2021 ). Although MSPs are indeed hallmark proteins of nematode sperm cells and are usually assumed to be entirely specific to sperm, there are in fact MSPs expressed in somatic cells and required for their mobility. Two different MSP homologs in Caenorhabditis elegans have cell and axonal migration RNAi phenotypes in male linker cells and hermaphroditic neurons, with one of them being expressed in linker cells ( S chmitz et al . 2007 ; S chwarz et al . 2012 ). Moreover, msp genes are expressed in C. elegans ADL chemosensory neurons ( O w et al . 2024 ), and are evolutionarily retained even in parthenogenetic nematode species lacking sperm ( H eger et al . 2010 ). Thus, nematodes express some msp genes somatically, which fits our observation here of msp , mfp2 , and duf236 gene expression in dissected intestines of adult A. ceylanicum . In addition, positively immunoregulated intestinal genes disproportionately encoded protein families with possible roles in host-parasite interactions. These families included: astacin, leishmanolysin, metallopeptidase, and trypsin-like proteases; TIMP protease inhibitors; ShK-related proteins; ASPs and ASPRs; SCVPs; and immunoglobulin domain-containing proteins ( Table 8 ). While most of these families were also enriched among ES genes, leishmanolysins, trypsins, and immunoglobulin domains were uniquely enriched here. Despite being expressed intestinally, only one of these immunoregulated genes had intestine-biased expression; instead, 258 were non-intestine-biased (3.67-fold over chance; p = 5.51•10 −78 ; Supplementary Table S15). View this table: View inline View popup Table 8. Protein motifs overrepresented in positively immunoregulated intestinal A. ceylanicum genes. Genes with types of immunoregulation other than positive intestinal had fewer notable protein families (Supplementary Table S15). The 137 negatively immunoregulated intestinal genes disproportionately encoded cysteine proteases and saposins, with saposins being uniquely enriched in this gene set (36-fold over chance; q = 9.94•10 −3 ). At least four C. elegans saposins have antimicrobial activity in vitro ( B anyai and P atthy 1998 ; R oeder et al . 2010 ; H oeckendorf and L eippe 2012 ; H oeckendorf et al . 2012 ); conversely, one saposin in A. ceylanicum has no antibacterial activity but does lyse blood cells in vitro ( H e et al . 2021 ). Negatively immunoregulated hookworm saposins might have either or both functions. Of the 26 positively immunoregulated non-intestinal genes, 15 encoded ASP proteins with CAP domains (46-fold over chance; q = 7.61•10 −19 ); 10 had non-intestine-biased expression (10.7-fold over chance; p = 1.12•10 −8 ). Both gene sets disproportionately encoded secreted proteins; neither set had prominently sex-biased expression. Immunoregulated genes have significantly male-biased expression Multicellular parasites such as hookworms are generally studied to understand mechanisms of infection common to both sexes, and indeed we ourselves collected both ES proteins and RNA from mixed-sex populations. However, males of the African tick Rhipicephalus appendiculatus excrete immunoglobulin-binding proteins that the males themselves do not seem to need, and that are instead required for coinfecting female ticks to feed on host blood efficiently ( W ang et al . 1998 ). This instance of sexual cooperation in a parasite made us wonder whether there existed male-biased or female-biased genes among our immunoregulated gene set. Using published RNA-seq data from A. ceylanicum adult males and females ( B ernot et al . 2020 ), we observed that 3,135 and 1,547 of our 33,190 predicted A. ceylanicum genes had male- or female-biased expression, respectively ( Table 6 ). Going on to check for overlaps of these gene sets with our immunoregulated gene set, we found that 50.1% of our positively immunoregulated intestinal genes (977/1,951; 5.3-fold over background; p = 0) were also male-biased, while only 11.6% of them (227/1,951; 2.5-fold over background; p = 3.34•10 −38 ) were female-biased ( Table 9 ; Supplementary Table S15). View this table: View inline View popup Download powerpoint Table 9. Gene categories overrepresented in A. ceylanicum immunoregulated genes. Such predominantly male-biased expression, along with the enrichment of three male-associated gene families (MSP, MFP2, and DUF236) in this gene set, raises the question of whether the changes in hookworm intestinal gene expression we observed with different host immunological backgrounds were actually due to our having harvested a higher proportion of male hookworms from normal than immunosuppressed hosts, leading to a male skew in putatively immunoregulated genes. We see two reasons why such bias is not sufficient to explain our observations. First, we only observed significant changes of gene activity in dissected intestines from 19-day adults, while observing no such changes in non-intestinal tissues from those same adults ( Table 6 ). If apparent immunoregulation of genes had actually been due to overlooked male bias in the hookworms we collected from normal hosts, one would expect to see at least as much (if not more) changed gene expression in non-intestinal tissues (which contained most, if not all, of the gonadal tissue from adults) as we saw from dissected intestines. The absence of significant immunoregulation in non-intestinal tissues (or in our 12-day whole animals) is inconsistent with such an artifact. Second, positively immunoregulated intestinal genes are not a simple subset of male-biased genes, as would be expected if male selection accounted for immunological changes of gene expression: 747 of these 1,951 immunoregulated genes had no sex bias, and 227 of them had female-biased expression. We conclude that the transcriptional immunoregulation we describe here, though dominated by male-biased genes, is nevertheless real. This suggests that male and female A. ceylanicum have different responses to the host immune system, and that such differences might account for the observed male-bias from our mixed-sex A. ceylanicum 19-day intestinal RNA-seq data. The host immune system affects ES gene expression Protein products of ES genes are thought to affect the host immune system, but whether the host immune system affects ES genes has been unclear. Comparing the ES gene set with immunomodulated gene sets, we observed significant overlaps ( Table 9 ). Out of 1,951 positively immunoregulated intestinal genes in 19-day hookworms, 153 also encoded ES proteins (27.1% of ES genes; 4.6-fold over chance; p = 1.19•10 −59 ). Of 26 positively immunoregulated non-intestinal genes, 13 were also ES genes (29-fold above chance; p = 7.47•10 −17 ); such expression might reflect synthesis and secretion of ES proteins by cephalic/pharyngeal glands ( H uang et al . 2020 ). The 153 positively immunoregulated intestinal ES genes disproportionately encoded astacin proteases, TIMP and TIL protease inhibitors, ShK-like proteins, ASPs, ASPRs, and SCVPs ( Table 10 ). Of these genes, 69 had ES gene homologs in A. caninum (20-fold enrichment; p = 6.00•10 −72 ), 24 in N. americanus (11-fold enrichment; p = 2.35•10 −18 ), and 24 in H. contortus (4.4-fold enrichment; p = 1.23•10 −9 ; Supplementary Table S16). As noted above, all of the above protein families may affect immunomodulation in hookworm hosts; in addition, astacin has been shown to enable tissue invasion in vitro by A. caninum ( W illiamson et al . 2006 ). Other immunoregulated ES genes also encoded proteins with possible functions in immunoregulation, antithrombosis, or digesting host tissue (Supplementary Table S6): the ASPs Acey -NIF-B ( M oyle et al . 1994 ; L o et al . 1999 ) and Acey -HPI ( D el V alle et al . 2003 ), two apyrases ( G uiguet et al . 2016 ; P ala et al . 2023 ), deoxyribonuclease II ( B ouchery et al . 2020 ), hyaluronidase ( H otez et al . 1992 ; Y ang et al . 2020 ), and superoxide dismutase ( K nox and J ones 1992 ; B rophy et al . 1995 ). View this table: View inline View popup Download powerpoint Table 10. Protein motifs overrepresented in positively immunoregulated intestinal A. ceylanicum ES genes. Discussion The ability of hookworms to suppress or evade their hosts’ immune systems and feed on their hosts’ blood and other tissues, for years, has motivated identifying hookworm genes whose products interact with the host, either by encoding ES proteins or by directly contacting host blood and tissues in the hookworm intestine ( W ei et al . 2016 ; A buzeid et al . 2020 ). Here we have identified ES proteins, intestine-biased genes, and immunoregulated genes in the hookworm A. ceylanicum , the last of which is unique to this study. Indeed, we hypothesized that hookworms regulate genes in response to the host immune system in order to suppress it, which motivated our immunosuppression/transcriptomic study here. Strongylid parasitic nematodes interact with the immune system despite generally not being blood-feeding ( B ansemir and S ukhdeo 1994 ; M c N eilly et al . 2017 ; P rice et al . 2019 ), so blood feeding is not necessary for such interactions. However, in the case of hookworms, our findings imply that interaction with the host immune system primarily occurs through contact of the hookworm intestinal lumen with host blood. Zoonotic A. ceylanicum productively infects both humans and other mammals, making it important to humans while also enabling laboratory studies of a true hookworm that is clinically relevant ( T raub 2013 ; C olella et al . 2021 ). We have analyzed both our new gene sets and previously identified gene sets ( W ei et al . 2016 ; B ernot et al . 2020 ; U zoechi et al . 2023 ), to identify traits encoded either by ES genes, intestinal genes, immuoregulated genes, or all three. To enable this work, we repredicted protein-coding genes in A. ceylanicum to the highest completeness so far achieved. We have greatly expanded the number of intestine-biased genes in A. ceylanicum and found them to be extensively homologous to intestine-biased genes in H. contortus ( L aing et al . 2013 ). We identified a mixture of functionally suggestive and poorly understood protein families in A. ceylanicum ES proteins and intestine-biased genes, observed genes that are immunoregulated in adult intestines (where they are exposed to host blood and circulating immune factors) but not other tissues, detected an unexpected male bias in positively immunoregulated intestinal genes, and defined a positively immunoregulated subset of ES genes that have a mosaic of conservation and species-specificity. On examination, it was possible to infer biologically coherent functions from what might seem to be a jumble of hookworm ES proteins. Immunosuppressors have been long suspected to be part of the ES protein repertoire, and we observed several protein types that could have this role. We also observed a pattern of diverse multigene families encoding ES proteins (ASPs, ASPRs, TTLs, and SCVPs); in other parasitic nematodes, such a pattern has been repeatedly seen both in ES proteins and in genetic diversity between strains or sibling species ( A buzeid et al . 2020 ; C ole et al . 2023 ; S tevens et al . 2023 ). It is not clear why this pattern exists; perhaps hookworms and other parasitic nematodes use diverse ES multigene families to survive unpredictably varying host immune systems by confusing their hosts with complex and varying mixtures of protein antigens, which leads parasitic nematodes to accumulate multigene families through balancing selection ( T homas and R obertson 2008 ; T ellier et al . 2014 ; E bert and F ields 2020 ). Another possible function that consistently emerged when examining ES proteins was inhibition of blood clotting. Despite being less often discussed and less obviously virulent, antithrombotics are at least as important for parasitism as immunosuppressants. Hookworm anticoagulants were first observed in 1904 ( L oeb and S mith 1904 ), and are likely to be necessary for sustained blood-feeding ( K vist et al . 2020 ; O liveira and G enta 2021 ; P ala et al . 2023 ). The strong overlap that we observed between immunoregulation and male-biased gene expression raises the question of whether hookworms have sex-specialized repertoires of genes that they express during infections ( C osta et al . 2009 ). There has been one striking instance (in the African tick R. appendiculatus ) where males and females interact differently with their hosts and the males act to promote female success during parasitism ( W ang et al . 1998 ). Our current data do not indicate whether such cooperation happens during hookworm infections, let alone whether the male-biased immunoregulated genes we describe are relevant to such hypothetical cooperation. However, such a bias might ensure that both sexes are present in a successful infection, which is required for reproduction. More extensive analysis to test for sexual cooperation during infections or sex-biased gene immunoregulation should be pursued for hookworms and other parasitic nematodes. Immunoregulated genes of A. ceylanicum have homologs in A. caninum , N. americanus , and H. contortus . The homologs of immunoregulated ES genes also encode ES proteins, suggesting that other parasitic nematodes may also have immunoregulated genes, and some findings indicate that they actually do. For the strongylid Teladorsagia circumcincta , being embedded in host mucosa upregulates ES genes and putative immunomodulatory genes ( M c N eilly et al . 2017 ; P rice et al . 2019 ). For the strongylid H. bakeri , infecting mouse hosts with colitis induces different ES proteins than normal hosts ( M aruszewska -C heruiyot et al . 2023 ). Finally, for the strongylid N. brasiliensis , recent transcriptomic and proteomic analyses shows genes that are positively or negatively regulated during infections of normal versus immunocompromised stat6 mutant mouse hosts, a subset of which encode ES proteins ( F erguson et al . 2023 ; F erguson et al . 2024 ). Thus, the immunoregulation we observe here for A. ceylanicum may be a general phenomenon found in many other parasitic nematodes. Supplementary Table, Figure, and File Legends Supplementary Table S1. A. ceylanicum RNA-seq libraries newly generated in this study. “RNA-seq library ID” provides a short abbreviation for each library; these abbreviations have been used for expression levels (TPMs), mapped read counts (reads), and differential gene expression analyses in later supplementary data tables. For each library, “SRA accession”, “BioProject accession” and “BioSample accession” provide accession numbers; “Reads”, “Total nt”, and “Read length in nt” give the number of reads, total sequence in nt, and read length; and “RNA-seq description” summarizes biological contents. Supplementary Table S2. Software used in this study. “Software” provides the name of each computer program or suite of computer programs; “Purpose” describes why this software was used here; “Main web site (URL) or code location” gives the primary Web site for this software; “Bioconda source (if used)” gives the bioconda web site for programs that were installed as bioconda environments; “Online documentation” gives the web site for detailed online manuals, if a given program has one. Publications and arguments for each program are cited and described in Methods. Supplementary Table S3. Published genomic data used in this study. Genome sequences, coding sequences, proteomes, and gene annotations of relevant nematodes were downloaded from WormBase ( D avis et al . 2022 ) or ParaSite ( H owe et al . 2017 ; L ee et al . 2017 ) and used for transcriptomic or proteomic analyses; they include Coghlan gene predictions and their corresponding A. ceylanicum genome assembly, along with UniProt ( U ni P rot 2023 ) and RefSeq ( O’L eary et al . 2016 ) proteome databases from highly GO-annotated model organisms. Four separate spreadsheets are given for data files of genomes, proteomes, CDS DNA sets, and gene annotations in GFF format. For each data file, “Species” gives the biological species described by the file, “Comments” describes the particular use(s) to which the data file was put in this study, and “URL” gives the Web source of the file. Supplementary Table S4. Published RNA-seq data of A. ceylanicum ( S chwarz et al . 2015 ; W ei et al . 2016 ; B ernot et al . 2020 ) and H. contortus ( L aing et al . 2013 ) used in this study. All RNA-seq files were downloaded from the European Nucleotide Archive (ENA). “Species” gives the file’s origin species. “Abbreviation” provides a short abbreviation for each library; these abbreviations have been used for expression levels (TPMs), mapped read counts (reads), and differential gene expression analyses in later supplementary data tables. “Biological condition (sex, developmental stage, tissue) and replicate number” describes biological content and replication. “Notes” describes any ambiguities that had to be resolved during analysis of the data. “Database” is uniformly ‘ENA’, but is included for completeness in the table. “Accession” and “URL” give SRA accession numbers and ENA Web sources for each file. Supplementary Table S5. LC-MS/MS analyses of two A. ceylanicum ES protein sets, E20201108-05 and E20201108-07. Data columns were generated by Proteome Discoverer 2.4; other details of the analysis are given in Methods. Supplementary Table S6. Annotations, RNA-seq expression, and differential gene expression for the A. ceylanicum v2.1 protein-coding gene set. Its data columns are as follows. Gene identifications and equivalencies Gene: A given predicted protein-coding gene in the A. ceylanicum genome assembly. All further data columns are pertinent to that particular gene. Gene_name: A human-readable gene name, where it exists (e.g., “ Acey -CP-1” instead of simply “Acey_s0154.v2.g3234”). These names are used in the main text to discuss genes of particular interest. Mapped_v1.0_gene: Any gene or genes from our previous v1.0 predictions which overlap the v2.1 gene here by least 1 nt of coding exon sequence in the A. ceylanicum genome. Although this criterion errs on the side of sensitivity and we have made no effort to filter out short overlaps, we expect that in practice this will identify extensive exon overlaps between an earlier v1.0 gene and its reprediction in v2.1. Mapped_Coghlan_gene: Any gene or genes from the previous A. ceylanicum gene predictions by Coghlan et al . ( C oghlan et al . 2019 ) which, when lifted over onto our A. ceylanicum genome assembly, overlap the v2.1 gene here by least 1 nt of coding exon sequence. Mapped_Uzoechi_gene: Any gene or genes from the recent A. ceylanicum gene repredictions by Uzoechi et al . ( U zoechi et al . 2023 ) which overlap the v2.1 gene here by least 1 nt of coding exon sequence. General traits of protein products Max_prot_size: The size of the largest predicted protein product. Prot_size: This shows the full range of sizes for all protein products from a gene’s predicted isoforms. Phobius: This denotes predictions of signal and transmembrane sequences made with Phobius 1.01 ( K Äll et al . 2004 ). ‘SigP’ indicates a predicted signal sequence, and ‘TM’ indicates one or more transmembrane-spanning helices, with N helices indicated with ‘(Nx)’. Varying predictions from different isoforms are listed. NCoils: This shows coiled-coil domains, predicted by Ncoils 2002.08.22 ( L upas 1996 ). Both the proportion of such sequence (ranging from 0.01 to 1.00) and the exact ratio of coiled residues to total residues are given. Proteins with no predicted coiled residues are blank. Psegs: This shows what fraction of a protein is low-complexity sequence, as detected by PSEG 1999.06.10 ( W ootton 1994 ). As with Ncoils, relative and absolute fractions of low-complexity residues are shown. Pfam: Predicted protein domains from Pfam 35.0 ( M istry et al . 2021 ), with family-specific significance thresholds. InterPro: Predicted protein domains from InterProScan 5.57-90.0 ( P aysan -L afosse et al . 2023 ). AMP: An antimicrobial peptide (AMP) gene annotation for v1.0 of our A. ceylanicum gene predictions, predicted by Irvine et al . ( I rvine et al . 2023 ), and mapped onto our v2.1 gene predictions here. GO_Biological: Annotations from the biological subset of Gene Ontology (GO) terms ( A shburner et al . 2000 ; C arbon et al . 2021 ), generated with EnTAP 0.10.7-beta ( H art et al . 2020 ). GO_Molecular: Annotations from the molecular subset of Gene Ontology (GO) terms ( A shburner et al . 2000 ; C arbon et al . 2021 ), generated with EnTAP 0.10.7-beta ( H art et al . 2020 ). GO_Cellular: Annotations from the cellular subset of Gene Ontology (GO) terms ( A shburner et al . 2000 ; C arbon et al . 2021 ), generated with EnTAP 0.10.7-beta ( H art et al . 2020 ). EggNOG_description: EggNOG descriptions ( H ernandez -P laza et al . 2023 ), generated with EnTAP 0.10.7-beta ( H art et al . 2020 ). EggNOG_KEGG: KEGG codes ( K anehisa et al . 2023 ), generated with EnTAP 0.10.7-beta ( H art et al . 2020 ). Orthologies of protein products OFind_Summary and OFind_Full The results for our OrthoFinder analysis ( E mms and K elly 2019 ) of orthologies between A. ceylanicum and the related nematodes A. caninum , C. elegans , H. contortus , H. bakeri , N. americanus , N. brasiliensis , Pristionchus pacificus , and T. circumcincta . For one of these species ( N. americanus ) two different proteomes were included: the original predicted proteome by Tang et al . ( T ang et al . 2014 ) labeled ‘necator_orig’, and the repredicted proteome by Logan et al . ( L ogan et al . 2020 ) labeled ‘necator_rev’. Two different views of these results are given: the summary lists taxa and gene counts, while the full results give individual gene names. ES- and gene-expression-related traits Intest_haemonchus: Homologous H. contortus genes (taken from OFind_Full ) that have intestine-biased gene expression, as computed by our analysis of previously published H. contortus RNA-seq data (Supplementary Table S4). Non-intest_haemonchus: Homologous H. contortus genes (taken from OFind_Full ) that have non-intestine-biased gene expression, as computed by our analysis of previously published H. contortus RNA-seq data (Supplementary Table S4). ES_component: A gene whose protein product was detected in at least one of our two ES mass spectrometry experiments, E20201108-05 and E20201108-07. Note that this was used as a binary (Boolean) classification for statistical analyses of gene set overlaps; see below for other such binary classifications. ES_observations: Observations of a gene’s protein product being present in either E20201108-05, or E20201108-07, or both. Coghlan-spec_ES: In our mass spectrometry analysis, our observation of a peptide mapping specifically to a Coghlan gene-encoded protein that was distinct from our v2.1 proteins by at least one amino acid residue, but whose Coghlan gene’s coding exons could then be lifted over to the coding exons of the v2.1 gene here ( Mapped_Coghlan_gene ). For each such mapping, the ES observations behind it are noted (either E20201108-05, or E20201108-07, or both). Uzoechi_ES: An ES-encoding gene detected by Uzoechi et al . ( U zoechi et al . 2023 ) whose coding exons mapped onto the coding exons of this v2.1 gene (in Mapped_Uzoechi_gene ). Note that Uzoechi et al . separately observed both male and female ES proteins, and those specific observations are given here. ES_a_caninum: Homology to an A. caninum gene encoding an A. caninum ES protein observed by Morante et al . ( M orante et al . 2017 ), extracted from OFind_Full . ES_necator_rev: Homology to an N. americanus gene encoding an N. americanus ES protein observed by Logan et al . ( L ogan et al . 2020 ), extracted from OFind_Full . ES_haemonchus: Homology to an H. contortus gene encoding an H. contortus ES protein observed by Wang et al . ( W ang et al . 2019 ), extracted from OFind_Full . Binary (Boolean) classifications of genes Male-biased: Annotation here indicates a gene with male-biased gene expression, as defined by ≥2-fold higher expression in males versus females, with a false discovery rate (FDR) of ≤ 0.01. Female-biased: Annotation here indicates a gene with female-biased gene expression, as defined by ≥2-fold higher expression in females versus males, with a false discovery rate (FDR) of ≤ 0.01. Intestine-biased: Annotation here indicates a gene with intestine-biased gene expression, as defined by ≥2-fold higher expression in 19-day intestinal tissue from normal hosts versus 19-day non-intestinal tissue from normal hosts, with a false discovery rate (FDR) of ≤ 0.01. Non-intestine-biased: Annotation here indicates a gene with non-intestine-biased gene expression, as defined by ≥2-fold higher expression in 19-day non-intestinal tissue from normal hosts versus 19-day intestinal tissue from normal hosts, with a false discovery rate (FDR) of ≤ 0.01. Any.19d.immunoreg: Annotation here indicates a gene with either intestinal or non-intestinal and either positively or negatively immunoregulated gene expression, as defined by ≥2-fold higher or lower expression in 19-day intestinal or non-intestinal tissue from normal hosts versus 19-day corresponding tissue from dexamethasone-immunosuppressed hosts, with a false discovery rate (FDR) of ≤ 0.01. Any.19d.pos.immunoreg: Annotation here indicates a gene with either intestinal or non-intestinal positively immunoregulated gene expression, as defined by ≥2-fold higher in 19-day intestinal or non-intestinal tissue from normal hosts versus 19-day corresponding tissue from dexamethasone-immunosuppressed hosts, with a false discovery rate (FDR) of ≤ 0.01. Pos.intest.immunoreg: Annotation here indicates a gene with intestinal positively immunoregulated gene expression, as defined by ≥2-fold higher expression in 19-day intestinal tissue from normal hosts versus 19-day intestinal tissue from dexamethasone-immunosuppressed hosts, with a false discovery rate (FDR) of ≤ 0.01. Neg.intest.immunoreg: Annotation here indicates a gene with intestinal negatively immunoregulated gene expression, as defined by ≥2-fold higher expression in 19-day intestinal tissue from dexamethasone-immunosuppressed hosts versus 19-day intestinal tissue from normal hosts, with a false discovery rate (FDR) of ≤ 0.01. Pos.non-intest.immunoreg: Annotation here indicates a gene with non-intestinal positively immunoregulated gene expression, as defined by ≥2-fold higher expression in 19-day non-intestinal tissue from normal hosts versus 19-day non-intestinal tissue from dexamethasone-immunosuppressed hosts, with a false discovery rate (FDR) of ≤ 0.01. Neg.non-intest.immunoreg: Annotation here indicates a gene with non-intestinal negatively immunoregulated gene expression, as defined by ≥2-fold higher expression in 19-day non-intestinal tissue from dexamethasone-immunosuppressed hosts versus 19-day non-intestinal tissue from normal hosts, with a false discovery rate (FDR) of ≤ 0.01. Neg.12d.immunoreg: Annotation here indicates a gene with negatively immunoregulated gene expression in 12-day young adults, as defined by ≥2-fold higher expression in 12-day young adults from dexamethasone-immunosuppressed hosts versus 12-day young adults from normal hosts, with a false discovery rate (FDR) of ≤ 0.01. (Note that no genes were observed with positively immunoregulated gene expression in 12-day young adults, so no ‘ Pos.12d.immunoreg ’ data column was needed.) Uzoechi_any_ES: Annotation here indicates a gene which was detected as encoding some sort of ES protein by Uzoechi et al . ( U zoechi et al . 2023 ). Practically, this means a gene with any annotation in Uzoechi_ES as encoding either a male ES (’Uzoechi_male_ES’), or a female ES (’Uzoechi_female_ES’), or both. Uzoechi_male.only_ES: Annotation here indicates a gene which was detected as encoding a male-specific ES protein by Uzoechi et al . ( U zoechi et al . 2023 ), annotated as solely ‘Uzoechi_male_ES’ in Uzoechi_ES . Uzoechi_female.only_ES: Annotation here indicates a gene which was detected as encoding a female-specific ES protein by Uzoechi et al . ( U zoechi et al . 2023 ), annotated as solely ‘Uzoechi_female_ES’ in Uzoechi_ES . Uzoechi_both_ES: Annotation here indicates a gene which was detected as encoding an ES protein in both males and females by Uzoechi et al . ( U zoechi et al . 2023 ), annotated as both ‘Uzoechi_male_ES’ and ‘Uzoechi_female_ES’ in Uzoechi_ES . Gene expression [X].TPM: For each individual RNA-seq data set (with ‘X’ denoting the data set’s abbreviation), this gives gene expression levels in TPM, computed by Salmon 1.9.0 ( P atro et al . 2017 ). Keys to all abbreviations are given in Supplementary Tables Sx and Sy. Biological replicates of RNA-seq samples are denoted by suffixes such as ‘_1’, ‘_2’, or ‘_3’. [X].reads: For each individual RNA-seq data set (with ‘X’ denoting the data set’s abbreviation), this gives numbers of mapped RNA-seq reads per gene, computed for individual RNA-seq data sets by Salmon 1.9.0 ( P atro et al . 2017 ), with fractional values rounded down to integers. Differential gene expression between biological conditions [X].vs.[Y].logFC: The fold-changes of gene expression between biological condition X and biological condition Y, expressed as log2 values, and with positive values representing greater expression in condition X. The values listed here are only those were computed to be significant using edgeR 3.36.0 ( R obinson et al . 2010 ), with multiple biological RNA-seq replicates for most conditions being compared, with all biological replicates being analyzed in a single edgeR run, and with significant results annotated for individual genes. Biological conditions of RNA-seq samples are abbreviated as shown in [X].TPM or [X].reads but without the replicate suffixes. [X].vs.[Y].FDR: The false discovery rate (FDR) for gene expression changes between biological condition X and biological condition Y, annotated for individual genes. The FDR for a given set of positive results is defined as that significance threshold which, if accepted, will lead to the entire set of positives having a collective false-positive rate no greater than the FDR; it therefore provides a way to correct for testing multiple hypotheses without rejecting excessive numbers of true positives. As with [X].vs.[Y].logFC , only changes that were computed to be significant by edgeR are listed. Supplementary Table S7. Statistical analyses of the overlaps between A. ceylanicum genes encoding protein motifs (or other traits) and A. ceylanicum genes encoding ES proteins. Each category of genes (e.g., genes encoding a particular protein motif or having a particular trait) was compared for its degree of overlap to a set of ES genes, and statistically analyzed for the non-randomness of this overlap by a two-tailed Fisher test. In situtations where many categories were compared at once (for instance, an entire set of protein motifs from Pfam, InterPro, or Phobius), p-values initially generated by Fisher testing were used to compute q-value significance scores which corrected for multiple hypothesis testing. Statistics are provided both for the set of 565 ES genes described in this paper (labeled “UMass_ES”) and for the set of 860 ES genes described by Uzoechi et al . ( U zoechi et al . 2023 ) (labeled “WashU_ES”). For each ES set, spreadsheets are given for analyses of overlaps with the following traits; signal or transmembrane domain organizations predicted by Phobius; protein motifs in Pfam; protein motifs in InterPro; and various binary comparisons with other gene traits (“Various”). Each analysis provides the following data: “Motif” denotes the specific protein motif (or other gene category) for which genes encoding it are being tested for nonrandomly high (or low) overlap with the ES gene set; “All_genes” gives the total number of v2.1 protein-coding genes within which overlaps were tested; “Motif_genes” gives the number of genes annotated with the protein motif (or other trait) being tested for overlap; “Class_genes” gives the number of ES genes being tested for overlap; “Motif.Class_overlap” gives the observed number of genes falling into both categories; “Exp_rand_overlap” gives the number of genes that would be expected to overlap purely randomly; “Enrichment” gives the ratio of observed versus random overlaps (note that this ratio can be lower than 1, and in fact can be as low as 0); “p-value” gives an initial stastistical significance for the observed overlap, computed by a two-tailed Fisher test; “q-value” gives, for cases of many comparisons at once (e.g., testing for all Pfam motifs simultaneously), a significance score that conservatively corrects for multiple hypothesis testing ( B ailey et al . 2009 ; N oble 2009 ). Note that q-values were not computed for simple binary comparisons of gene traits listed in “Various”, which are annotated for A. ceylanicum genes in Supplementary Table S6 , and defined in its table legend: Intestine-biased; Non-intestine-biased; Pos.intest.immunoreg; Neg.intest.immunoreg; Pos.non-intest.immunoreg; Neg.non-intest.immunoreg; Male-biased; Female-biased; Uzoechi_any_ES; Uzoechi_male.only_ES; Uzoechi_female.only_ES; and Uzoechi_both_ES. Also, again note that highly significant overlaps can be either higher or lower than the randomly expected genome-wide background rate. Supplementary Table S8. Annotations, RNA-seq expression, and differential gene expresssion for the H. contortus protein-coding gene set. We annotated predicted protein products with N-terminal signal sequences, conserved protein domains, orthologies to genes in related nematode species, and Gene Ontology (GO) terms describing biological and molecular functions. Protein-coding genes were predicted by Doyle et al . ( D oyle et al . 2020 ). Since the annotation methods we used for this H. contortus proteome were identical to those we used for our A. ceylanicum v2.1 proteome, almost all the data columns used here are equivalent to those in Supplementary Table S6 . One data column unique to this table is “Hco_ES”, which denotes H. contortus genes previously demonstrated by Wang et al . ( W ang et al . 2019 ) to encode ES proteins. Supplementary Table S9. Annotations for protein-coding gene sets of A. caninum and N. americanus . We annotated predicted protein products with N-terminal signal sequences, conserved protein domains, orthologies to genes in related nematode species, and Gene Ontology (GO) terms describing biological and molecular functions. Protein-coding genes were predicted for A. caninum by Coghlan et al . ( C oghlan et al . 2019 ) and for N. americanus by Logan et al . ( L ogan et al . 2020 ). Since the annotation methods we used for these proteomes were identical to those we used for our A. ceylanicum v2.1 proteome, almost all the data columns used here are equivalent to those in Supplementary Table S6 . Two data columns unique to these tables are Acan_ES and Necator_ES , which respectively denote A. caninum or N. americanus genes previously demonstrated by Morante et al . ( M orante et al . 2017 ) or Logan et al . ( L ogan et al . 2020 ) to encode ES proteins. Supplementary Table S10. Statistical analyses of the overlaps between A. caninum , N. americanus , or H. contortus genes encoding protein motifs (or other traits) and A. caninum , N. americanus , or H. contortus genes encoding ES proteins. ES gene annotations are taken from Supplementary Tables S8 and S9. Statistical significances of overlaps between motif/trait genes and ES genes were computed and described as in Supplementary Table S7 . Supplementary Table S11. Statistical analyses of overlaps between pairs of A. ceylanicum gene sets, with A. ceylanicum genes encoding ES proteins versus A. ceylanicum genes having various homologies to either ES genes or any genes in A. caninum , H. contortus , or N. americanus . “ES_a_caninum”, “ES_haemonchus”, and “ES_necator_rev” denote sets of A. ceylanicum genes with homology to ES genes in A. caninum , H. contortus , or N. americanus ; “ES_Acan.or.Hco.or.L2020” denotes a set of A. ceylanicum genes with homology to ES genes in any of these three species. “Acan_homology”, “Haemonchus_homology”, and “Necator_homology” denote sets of A. ceylanicum genes with homology to any genes (ES protein-encoding, or not) in A. caninum , H. contortus , or N. americanus ; “Acan.Hco.Nec_homology” denotes a set of A. ceylanicum genes with homology to any genes in any of these three species. The ES gene sets are either from this study (“all_UMass_ES”) or from Uzoechi et al . ( U zoechi et al . 2023 ) (“all_WashU_ES”). Subsets of these ES gene sets that lack homologies to known ES genes in related parasites are denoted with “non_AcanES_homol_[ES]” (for A. ceylanicum ES genes lacking homologies to A. caninum ES genes), “non_HcoES_homol_[ES]” (for A. ceylanicum ES genes lacking homologies to H. contortus ES genes), “non_NecES_homol_[ES]” (for A. ceylanicum ES genes lacking homologies to N. americanus ES genes), or “non_anyES_homol_[ES]” (for A. ceylanicum ES genes lacking homologies to ES genes in any of the three other species). Statistical significances of overlaps between homologous genes and ES genes were computed and described as in Supplementary Table S7 . Supplementary Table S12 . The frequencies with which RNA-seq reads (either from our new RNA-seq libraries listed in Supplementary Table S1 , or from previously published RNA-seq libraries listed in Supplementary Table S4 were mapped to A. ceylanicum v2.1 genes by Salmon 1.9.0 ( P atro et al . 2017 ). Supplementary Table S13. Statistical analyses of the overlaps between A. ceylanicum genes encoding protein motifs (or other traits) and A. ceylanicum genes with either intestine-biased or non-intestine-biased gene expression. Statistical significances of overlaps between motif/trait genes and intestine-biased or non-intestine-biased genes were computed and described as in Supplementary Table S7 . In addition, pairwise overlaps between intestine- or non-intestine-biased gene sets and other gene categories are provided in the ‘Various’ spreadsheet; since these do not involve multiple comparisons of entire motif sets, only p-values rather than q-values are computed for these overlaps. A. ceylanicum gene categories in “Various” are: “Intest_haemonchus”, genes with homology to H. contortus genes with intestine-biased expression; “Non-intest_haemonchus”, genes with homology to H. contortus genes with non-intestine-biased expression; “WashU-intestine-biased”, genes with intestine-biased expression computed from previously published A. ceylanicum RNA-seq data; “WashU-non-intestine-biased”, genes with non-intestine-biased expression computed from previously published A. ceylanicum RNA-seq data ( Supplementary Table S4 ) ( W ei et al . 2016 ; B ernot et al . 2020 ). Supplementary Table S14 . Statistical analyses of the overlaps between H. contortus genes encoding protein motifs (or other traits) and H. contortus genes with either intestine-biased or non-intestine-biased gene expression. Statistical significances of overlaps between motif/trait genes and intestine-biased or non-intestine-biased genes were computed and described as in Supplementary Table S7 . Supplementary Table S15. Statistical analyses of the overlaps between A. ceylanicum genes encoding protein motifs (or other traits) and A. ceylanicum genes with positively or negatively immunoregulated intestinal or non-intestinal gene expression. Statistical significances of overlaps between motif/trait genes and positively immunoregulated intestinal genes were computed and described as in Supplementary Table S7 . In addition, pairwise overlaps between immunoregulated gene sets and other categories (such as “Male-biased”) are provided in the “Various” spreadsheet; since these do not involve multiple comparisons of entire motif sets, only p-values rather than q-values are computed for these overlaps. Supplementary Table S16. Statistical analyses of the overlaps between A. ceylanicum genes encoding protein motifs (or other traits) and A. ceylanicum genes encoding ES proteins that also have positively immunoregulated gene expression in 19-day intestines. Statistical significances of overlaps between motif/trait genes and positively immunoregulated ES genes were computed and described as in Supplementary Table S7 . In addition, pairwise overlaps between the positively immunoregulated intestinal ES gene set and other categories (such as “Male-biased”) are provided in the “Various” spreadsheet; since these do not involve multiple comparisons of entire motif sets, only p-values rather than q-values are computed for these overlaps. Download figure Open in new tab Download figure Open in new tab Supplementary Figure 1. Gene expression in A. ceylanicum . Gene activity is shown for all 33,190 A. ceylanicum genes, with biological replicates on the x-axis and individual genes on the y-axis. Expression levels are in TPM (log10). In Supp. Fig. 1A , replicates are ordered as in Figure 2 ; in Supp. Fig. 1B , replicates are ordered by their similarity of expression (and a dendrogram for their similiaries is shown along the top x-axis). Genes sharing similar patterns of expression are split into 10 clusters. Biological replicates are: young 12-day hookworm adults from normal hosts (YA_12dpi_noDEX); young 12-day adults from immunosuppressed hosts (YA_12dpi_DEX); dissected 19-day intestines from mature hookworm adults in normal hosts (intestines_19dpi_noDEX); dissected 19-day intestines in immunosuppressed hosts (intestines_19dpi_DEX); dissected 19-day intestines in normal hosts (non.intestines_19dpi_noDEX); dissected 19-day non-intestinal tissues in immunosuppressed hosts (non.intestines_19dpi_DEX); previously published adult male intestine (WashU_male_intestine); published adult males (WashU_adult_male); and published adult females (WashU_adult_fem). These heatmaps include two biological replicates (19-day nonDEX intestine replicate 2 and 19-day DEX intestine replicate 2) that clustered anomalously with replicates 1 and 3 of intestinal RNA-seq samples with opposite nonDEX versus DEX status. We interpret this to mean that labeling for the nonDEX/DEX status of these samples was accidentally reversed between RNA harvesting and RNA-seq. We thus omitted these two samples from differential gene expression analysis. Supplementary File 1. An R script used in batch mode for differential gene expression with edgeR 3.36.0 and R 4.1.3. Data Availability A. ceylanicum transcriptomic data have been archived in the Sequence Read Archive ( K atz et al . 2022 ) with NCBI BioProject accession PRJNA1045065, and with BioSample accessions SAMN38429478, SAMN38440155, SAMN38440168, SAMN38440169, SAMN38440219, and SAMN38440220. Mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository ( P erez -R iverol et al . 2022 ) with the dataset identifiers PXD047871 and PXD047879. Protein-coding gene predictions for A. ceylanicum have been archived at the Open Science Framework ( https://osf.io/dxfsb ). Funding This work was supported by the National Institutes of Health (NIH)’s National Institute of Allergy and Infectious Diseases (NIAID; https://www.niaid.nih.gov ) grants 1R21-AI111173 and R01-AI056189 to R.V.A., by NIH’s Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD; https://www.nichd.nih.gov ) grant 1R01-HD099072 to R.V.A., and by Cornell startup funds to E.M.S. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests The authors have declared that no competing interests exist. Acknowledgments We thank Titus Brown and the Michigan State University High-Performance Computing Center (supported by U.S. Department of Agriculture grant 2010-65205-20361 and NIFA-National Science Foundation (NSF) grant IOS-0923812) for computational support; additional computing was enabled by start-up and research allocations from NSF XSEDE (TG-MCB180039 and TG-MCB190010). 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