Distinctive signatures of pathogenic and antibiotic resistant potentials in the hadal microbiome.

"the metagenomic and amplicon sequence data are deposited in the china national genebank database (cngbdb) database under the accession id: cnp0001961 (additional file 2 : dataset s1).; the first round of hmmscan (hmmer3) search of orfs with the option ''-cutga'' against a self-constructed hmms subdatabase of args (i e argfams) which was built from pfam (v 30 0) and tigrfams based on string match in their functional annotations to one of the keywords (additional file 2 : dataset s2).; the identified args were then classified into 12 types including aminoglycoside beta-lactam bleomycin chloramphenicol daunorubicin macrolide-lincosamide-streptogramin (mls) multidrug quinolone tetracycline trimethoprim vancomycin unclassified followed by further classification into 187 subtypes (additional file 2 : dataset s3).; we further classified all the mges identified into 6 types (i e integrase resolvase plasmid recombinase conjugation transposase) and 179 subtypes (additional file 2 : dataset s4) based on the above keywords and the names of gene or gene family in the pfam respectively.; most of the virulence genes found are commonly shared by all hadal metagenomes including genes encoding several hemolysins and repeats-in-toxin (rtx) proteins (fig 2 a; additional file 2 : dataset s5).; we observed a much higher number of vfg types in the water metagenomes than sediment metagenomes while a unique spectrum of virulence factors was noticeable in the deepest sediment (sm10898 additnal file 1 : fig s3 additional file 2 : dataset s6).; to explore the collection of args or antibiotic resistome in the mariana trench we used args-oap v2 0 [ ] to analyze the clean reads of all sediment metagenomes to quantify a broad spectrum of known args (additional file 2 : dataset s7).; to check which hgt mechanisms may contribute to the hadal adaptation and the evolution of the mariana trench microbiota we predicted mobility genes based on a strategic two-step hmmscan search against two concatenated hmm databases with only mobility genes and with all functional genes respectively (additional file 2 : dataset s8).; to explore the spreading potentials of args and vgs of the sediment microbiome of mariana trench we compared the co-occurrence instances between args (additional file 2 : dataset s9) mges and vgs on the same metagenome-assembled contigs (fig 5 a).; datasets s1 : metagenomic data information.; dataset s2 : key words which were used to extract the hmm models to construct the argfams from pfam (v 30 0) and tigrfams.; dataset s3 : arg types and subtypes' information of domain based annotation result.; dataset s4 : mge types and subtypes' information.; dataset s5 : the number of toxin genes predicted from the sediment metagenomes based on dbeth.; dataset s6 : the number of toxin genes predicted from the sediment metagenomes based on vfdb.; dataset s7 : relative abundance of known args in the sediment metagenomes based on args-oap v2 0 pipeline analysis.; dataset s8 : number and distribution of mges genes predicted from the sediment metagenomes based on mgefams.; dataset s9 : number of args predicted from the sediment metagenomes based on argfams."

"Declarations Ethics approval and consent to participateThe manuscript does not contain data collected from humans and animals. Consent for publicationNot applicable. Competing interestsThe authors declare that they have no competing interests. Competing interests The authors declare that they have no competing interests."

"Funding This work was supported by the National Key Research and Development Program of China (Grant No. 2018YFE0110500 to F.J.), The National Natural Science Foundation of China (Grant No. 51908467 to F.J. and Grant No. 31970129 and Grant No. 31800128 to L.T.), and Zhejiang Provincial Natural Science Foundation of China (Grant No. LR22D010001 to F.J. and Grant No. LR20C010001 to L.T.)."