Evaluative Profiling of Arsenic Sensing and Regulatory Systems in the Human Microbiome Project Genomes

The influence of environmental chemicals including arsenic, a type 1 carcinogen, on the composition and function of the human-associated microbiota is of significance in human health and disease. We have developed a suite of bioinformatics and visual analytics methods to evaluate the availability (presence or absence) and abundance of functional annotations in a microbial genome for seven Pfam protein families: As(III)-responsive transcriptional repressor (ArsR), anion-transporting ATPase (ArsA), arsenical pump membrane protein (ArsB), arsenate reductase (ArsC), arsenical resistance operon transacting repressor (ArsD), water/glycerol transport protein (aquaporins), and universal stress protein (USP). These genes encode function for sensing and/or regulating arsenic content in the bacterial cell. The evaluative profiling strategy was applied to 3,274 genomes from which 62 genomes from 18 genera were identified to contain genes for the seven protein families. Our list included 12 genomes in the Human Microbiome Project (HMP) from the following genera: Citrobacter, Escherichia, Lactobacillus, Providencia, Rhodococcus, and Staphylococcus. Gene neighborhood analysis of the arsenic resistance operon in the genome of Bacteroides thetaiotaomicron VPI-5482, a human gut symbiont, revealed the adjacent arrangement of genes for arsenite binding/transfer (ArsD) and cytochrome c biosynthesis (DsbD_2). Visual analytics facilitated evaluation of protein annotations in 367 genomes in the phylum Bacteroidetes identified multiple genomes in which genes for ArsD and DsbD_2 were adjacently arranged. Cytochrome c, produced by a posttranslational process, consists of heme-containing proteins important for cellular energy production and signaling. Further research is desired to elucidate arsenic resistance and arsenic-mediated cellular energy production in the Bacteroidetes.


Introduction
High-throughput technologies for assaying biological macromolecules and metabolites are providing wealth of data on the structure, function, and condition-induced changes within host-associated microbial communities. 1 The influence of environmental chemicals including arsenic, a type 1 carcinogen, on the composition and function of the human-associated microbiota is of significance in human health and disease. 2 The data from the Human Microbiome Project (HMP) include genome sequences and functional annotations for over 1000 microbial isolates obtained from diverse body sites of healthy adults. [3][4][5] There is an urgent need for data analytics (modeling and simulation, statistical analysis, and visual analytics) of the wealth of data on the human microbiome for new types of treatment as well as mechanisms of chronic diseases. [6][7][8] The results from data analytics of microbiome data hold promise to advance knowledge of how the human microbiota at body sites respond to ubiquitous environmental chemicals such as arsenic.
The overall theme of our research is to identify and evaluate microbial gene clusters that are equipped for stress response. 9 In this article, we report the integration of data on the availability and abundance of genes for arsenic stress response in microbial genomes. We reason that the integration of availability (presence or absence) and abundance of genes for functions can be informative on the microbe's potential to perform the functions. In the case of influences of arsenic on the human microbiome, knowledge on the availability and abundance of arsenic stress response genes will guide further research on the pre-systemic metabolism of arsenic by the microbiota at the body site.
Arsenic is a naturally occurring environmental chemical, and drinking water and dietary intake are two main routes through which human beings are exposed to it. 10,11 Pentavalent (arsenate) and trivalent (arsenite) inorganic arsenic species perturbs the normal cell function. 12 The ubiquitous natural occurrence of arsenic means that cells from all domains of life must develop molecular and phenotypic mechanisms to respond to arsenic-induced stress. [13][14][15] Ingested arsenic is a cause of cancers of the skin, lungs, bladder, and kidneys. 16 Gut microbial metabolism of arsenate produces the more absorbable and toxic arsenite. The genome sequences of single isolates and microbial communities encode mechanisms by which gut microbiota transforms ingested arsenic to more toxic trivalent methylated and thiolated arsenicals prior to their metabolism in human cells. 17,18 Therefore, to make progress on elucidating pre-systemic metabolism of arsenic, it is necessary to identify microbes of the human microbiota with genes for sensing and regulating arsenic.
Exposure of the human microbiota to arsenic presents an unfavorable environment to microbial cells. In microbial genomes, several genes function in the sensing and regulation of inorganic arsenic. We are interested in the genes encoding arsenic resistance operon, the aquaporins, and the universal stress proteins (USPs). These genes encode function for sensing and/or regulating (resistance) arsenic content in the bacterial cell. 19 The best-characterized arsenic genes include As(III)responsive transcriptional repressor (arsR), anion-transporting ATPase (arsA), arsenical pump membrane protein (arsB), arsenate reductase and related proteins, glutaredoxin family (arsC), arsenical resistance operon trans-acting repressor (arsD), arylsulfatase family, member H (arsH), putative membrane permease (ArsP), and As(III)-S-adenosylmethionine methyltransferase (arsM). 20 The genes for conversion of arsenate to arsenite and arsenite extrusion from the cell are typically organized as operons, such as arsRBC, arsRABC, and arsRDABC, but the genes can also exist alone. 20 Proteins for water and/or glycerol transport across cellular membranes termed aquaporins can also function in arsenic transport. 21 The USP family is a protein family known to enable bacteria, archaea, fungi, viridiplantae, and certain metazoans that respond to stresses. [22][23][24] The USP family includes proteins that contain 140-160 amino acid (aa) USP domain [PF00582 (or Pfam00582) in the Pfam database]. [22][23][24] The domain architecture of USPs can be (i) one USP domain, (ii) two USP domains in tandem, or (iii) one or two USP domains together with other functional domains including transporters, kinases, permeases, transferases, and bacterial sensor. 24,25 In Exiguobacterium sp. PS, a Gram-positive bacteria that lacks arsenic reductase activity, a USP was induced by arsenate stress. 26 The uspA of Escherichia coli has been evaluated as a sensor to detect chemical toxicants. 27 The availability of diverse data from HMP allows for secondary data analytics including constructing profiles of functional annotations for genes involved in arsenic sensing and regulation in the HMP genomes collection. Therefore, we report the development of a genome profiling scheme based on the availability of functional annotations for seven Pfam protein families, including known arsenic resistance operon proteins, aquaporins, and USPs. A list of 62 genomes from 18 genera was identified including 12 genomes in the HMP genomes collection. Several noteworthy findings could be a basis for further investigations. For example, in multiple Bacteroides genomes, a gene for arsenic binding and transfer (arsD) is adjacent to a gene for cytochrome c biogenesis protein. Cytochrome c, produced by a posttranslational process, consists of heme-containing proteins important for cellular energy production and signaling. 28,29 Previous reported research on Bacteroides and arsenic appears to be limited to phenotypic characterization of susceptibilities to arsenate in which 25% of strains in the Bacteroides fragilis group, which included Bacteroides thetaiotaomicron, were resistant to 0.01 M arsenate. 30 Further research is desired to elucidate arsenic resistance and arsenic-mediated cellular energy production in the Bacteroidetes.

Methods
Construction of functional annotation profiles for arsenic stress response of microbial genomes. We assembled a list of protein family functions (Pfam) that are known to participate in the metabolism of arsenic and in stress response in bacteria and archaea. The Pfam identifiers, names, and common abbreviation of the proteins are Pfam02374 . Genomes with a profile of interest were further grouped into relevance annotation (eg, agriculture, biotechnology, human pathogen, and medical) provided by the Integrated Microbial Genomes (IMG) system. When relevance is not annotated, we tagged the genome as "Not_Reported." A binary matrix that encodes the presence (1) or absence (0) of a relevance annotation for selected genomes was constructed. The binary matrix was visualized with matrix2png. 31 Integration of availability and abundance of genes for arsenic metabolism and USPs. Genes annotated for presence of the above seven protein families in microbial genomes were initially retrieved from the IMG system (http://img.jgi. doe.gov/) in December 2011 (IMG version 3.5). 32 The datasets were downloaded as Excel spreadsheets and integrated in a visual analytics software (Tableau Desktop Professional, Seattle, WA). The dataset includes several fields including the genome name (Genome) and the gene object identifier (Gene Object ID). The visual analytics tool displayed the availability (presence or absence) and abundance (number of genes annotated with the Pfam function) of each microbial genome. A list of reference genomes sequenced by the HMP was obtained from the HMP catalog (http://www.hmpdacc. org/catalog/). Because B. thetaiotaomicron is a dominant symbiont of the gut of humans and other mammals, 33 we decided to determine the abundance of genes for the arsenic resistance operon (arsRABCD) in the Bacteroides genomes in the dataset. A visualization was also generated to provide an overview of the abundance of the arsenic resistance genes in Bacteroides genomes.
Functional associations of ArsD encoded transcription units in B. thetaiotaomicron. The gene content of the transcription unit with arsenic-associated genes was determined for B. thetaiotaomicron using the BioCyc database collection of pathway/genome databases (PGDBs). 34 In BioCyc, a transcription unit is defined as a set of one or more genes that are transcribed to produce a single messenger RNA. Our particular interest is in multigene transcription units. Based on the observed functions in the transcription units, the presence of two Pfam functions in a chromosomal cassette was determined with the Cassette search tool of the IMG system. 32 In the IMG system, a chromosomal cassette is defined as a stretch of protein coding genes with intergenic distance lesser than or equal to 300 base pairs.
Known and predicted functional associations of proteins encoded in a transcription unit were retrieved from the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. 35 With this approach, we expect that the STRING database will provide a score for gene neighborhood evidence for genes in a transcription unit. Other types of evidence that are used in the STRING database to calculate a combined score are gene fusion, co-occurrence, co-expression, experiment, databases, text mining, and homology. 35

Results
Arsenic stress response profiles for genomes. A sevendigit binary code was assigned to 3,274 genomes (119 archaea, 3033 bacteria, and 122 eukaryota) obtained from the IMG system. The order of the seven Pfam families in the binary code is ArsA, ArsB, ArsC, ArsD, ArsR, Aqp, and Usp (Table 1). As functional annotations of genes could change, we selected only genomes that have the complete profile (111111111). A total of 62 microbial genomes from 18 genera had a binary code in which all the seven Pfam families were present. We further grouped the genomes according to their relevance (eg, agriculture, biotechnology, human pathogen, and medical) to help direct further research. A subset of 57 genomes with the complete profile was mapped to 22 assignments of relevance. Additionally, five genomes did not have an assignment of relevance and their assignment was designated "Not_Reported". A visualization of the matrix of 23-digit binary signatures was constructed for 62 genomes (Fig. 1).
The 12 HMP reference genomes with the complete profile were grouped in the body sites: gastrointestinal tract, skin, and skin wound. The genomes with the complete binary profile from the human gastrointestinal tract were Citrobacter sp. 30_2, E. coli MS 115-1, E. coli MS 198-1, Lactobacillus fermentum ATCC 14931, and Providencia stuartii ATCC 25827. Additionally, the selected genomes based on the complete seven-digit profile and isolated from the skin were five strains of Staphylococcus epidermidis, Staphylococcus hominis SK119, and Rhodococcus erythropolis SK121. The locus tags for genes encoding the protein families are presented in Table 2. The locus tags are presented in the sequence of the arsRDABC operon ( Table 2). The arrangement of the genes with reference to their function is presented in Table 3. In Citrobacter sp. 30_2, two arsenic resistance gene clusters were identified with the same gene order of arsRDABC. Overall, a pattern in Table 3 is that arsA and arsD when present are adjacent for all the genomes from the four Gram-negative bacteria.
However, in L. fermentum ATCC 14931, the gene cluster order was arsRABDC.
Integration of availability and abundance of genes for arsenic sensing and regulation. The integration of data fields from several data sources was accomplished through visual analytics tasks. Figure 2 is a visualization that integrates the data on binary code; body site; genome; and the availability of Pfam annotations and abundance (number of genes) for 12 reference genomes sequenced by the HMP. Several patterns can be identified from Figure 2. As gastrointestinal pre-systemic metabolism is an essential step of arsenic metabolism in humans, we further investigated the abundance of arsenic resistance genes in 43 Bacteroides genomes (Fig. 3). There were several noteworthy findings from the visualization including  are, respectively, labeled as TUJXV-83 and TUJXV-442 in BioCyc, respectively. These transcription units have nine and six genes, respectively ( Fig. 4A and B). As shown in Figure 4C The gene for ArsD proteins (BT_0117 and BT_0801) of B. thetaiotaomicron VPI-5482 was selected as input proteins for generation of protein-protein interaction network. As expected, the generated networks (Fig. 4D)    and BT_0116 (arsA) has multiple types of evidence and is expected. A predicted interaction of BT_0120 (redox-active disulfide protein) had co-occurrence and fusion evidence types with BT_0112 (a permease) and BT_0110 (hypothetical protein), respectively. There was experimental evidence for the interaction between homologs of BT_0802 (arsA) and ileS (BT_0806; isoleucyl-tRNA synthetase).

Discussion
We have provided an integrated view of relevance of 62 genomes from 18 genera with genes for arsenic operon, aquaporin, and USPs (Fig. 2). A set of 12 bacteria genomes in the HMP collection 5 was identified to have genes encoding seven protein families defined in this research as relevant to arsenic sensing and regulation ( Citrobacter sp. 30_2 is a Gram-negative isolate from an intestinal biopsy specimen of patient with Crohn's disease. 36 The Citrobacter genus are rod shaped, motile, non-spore forming members of the family Enterobacteriaceae that use citrate as their sole source of carbon. 37,38 In terms of arsenic metabolism, Citrobacter sp. NC-1 isolated from soil contaminated with arsenic at levels as high as 5,000 mg. As kg -1 was able to reduce 20 mM arsenate within 24 h. 39 A comparison of Citrobacter sp. 30_2 and Citrobacter UC1CIT strains from a premature infant revealed the presence of an arsenic operon unique to strain 30_2. 36 The two E. coli strains identified are part of the project on human gut microbiota and Crohn's disease (http://genome.wustl.edu/projects/). An indication that the genomic composition of E. coli MS 115-1 is equipped for environmental fitness is the presence of the clpK gene for thermal resistance in Klebsiella pnuemoniae. 36 E. coli MS 115-1 is one of the two E. coli strains with the clpK gene. In Table 3, we observed that arsA and arsD were adjacent for all the four Gram-negative bacteria. However, in L. fermentum ATCC 14931, the arsB and arsD were adjacent. A systematic evaluation of more than 19,000 bacterial genomes could provide additional examples of this gene adjacency. Functional analysis with molecular techniques could also elucidate impact of the adjacency on arsenic extrusion.
We have included the USPs as markers for arsenic exposure because of (i) prior research that support induction of USPs by arsenic and (ii) proximity of arsenic-associated genes and genes for USPs. Arsenite early exposure (15 minutes) induced the transcription of two usp genes in Herminiimonas arsenicoxydans, a bacterium isolated from arsenic-contaminated sludge. 40 A usp gene and an arsenic resistance operon are located on an antibiotic-resistant island in the genome of Acinetobacter baumannii, an opportunistic pathogen that causes nosocomial infections. 41 We have observed that the genome of Bacillus cereus Q1 contains a usp gene that is adjacent and in the same transcription direction with a gene with predicted function for HTH ArsR-type DNA-binding domain (Inter-Pro Database Identifier: IPR001845). 9 Further research is needed to better define the relationship between expression of USP genes and the level of arsenic exposure. Additionally, investigations are desired in the context of arsenic sensing to compare the speed of expression of USP genes and arsenic resistance operon (ars) genes.
In the Gram-negative colon inhabiting B. thetaiotaomicron VPI-5482, two transcription units include arsenic resistance genes (ars) (Fig. 4). Investigations to confirm these genes would help define mechanisms for arsenic sensing and regulation by B. thetaiotaomicron VPI-5482, which is able to acquire and utilize indigestible dietary polysaccharides. 42 Multiple copies of ars genes in B. thetaiotaomicron VPI-5482 are consistent with expansion of paralogous genes and the species environmental sensing abilities needed to adapt to changing ecosystems. 33 Only genomes categorized under the phylum Bacteroidetes contain genes encoding for the cytochrome c biogenesis protein adjacent to the arsD gene protein is adjacent to the arsD gene only genomes of the Bacteroidetes phylum (Fig. 3). Cytochrome c, produced by a posttranslational process, consists of heme-containing proteins important for cellular energy production and signaling. 28,29 The arsD controls the maximal expression of the arsenic-resistant operon (arsRDABC). 43 The ArsD metallochaperone protein delivers arsenite to ArsA efflux pump. 44,45 The significance of the adjacency of cytochrome c biogenesis protein and the metallochaperone needs further investigation. In Shewanella putrefaciens strain CN-2, a subunit of c-type cytochrome (CymA) that is present in anaerobic conditions functions in conjunction with a known respiratory arsenate reductase. 46 Through additional functional annotation data curation, we noted the presence of a gene for mercuric transport protein (Locus Tag: BT_0113; UniProt Accession: Q8ABJ7) in one of the BioCyc transcription units (TUJXV-83) of the B. thetaiotaomicron VPI-5482 (Fig. 4). Predictions available at OrthoDB indicate that the gene encodes a mercuric transport protein (http://cegg.unige.ch/orthodb/results?searchtext=Q8ABJ7). 47 Genes BT_0112 and BT_0114 encode transport functions. The proteins encoded by the genes BT_0112, BT_0113, and BT_0114 could be investigated for mechanisms of heavy metal transport in B. thetaiotaomicron.
The focus of the evaluative profiling scheme was limited to seven Pfam annotations. Thus, certain functions that are arsenic associated would not be evaluated. For example, in the Bacteroides genomes, annotation for ArsB (Pfam02040; arsB) was not observed (Fig. 3). The annotation available in the genomes was the ACR3 form. Furthermore, in L. fermentum ATCC 14931, arsC (HMPREF0511_1135) in the arsenic resistance operon (HMPREF0511_1131 to HMPREF0511_1135) was not annotated with the Pfam family Pfam0396, but the annotation observed was Pfam01451. Our evaluative scheme assessed the arsenic reductase genes annotated with Pfam03960.
Further development of the evaluative profiling for arsenic sensing and regulation would be more comprehensive using the arsenic-related gene families: cytoplasmic AsV reduction (ars), periplasmic AsV reduction (arr), arsenite oxidation (aio), and arsenite methylation (arsM). 48 Finally, the evaluative profiles will account for instances where multiple Pfam families map to a gene as with arsC and arsB.

Conclusion
In conclusion, we have developed a suite of bioinformatics and visual analytics methods to evaluate the availability (presence or absence) and abundance of functional annotations in a microbial genome for seven Pfam protein families: As(III)-responsive transcriptional repressor (ArsR); aniontransporting ATPase (ArsA); arsenical pump membrane protein (ArsB); arsenate reductase (ArsC); arsenical resistance operon trans-acting repressor (ArsD); water/glycerol transport protein (aquaporins); and USP. We identified 62 genomes from 18 genera that have genes for all the seven protein families. Our list included 12 genomes in the HMP reference genomes from the following genera Citrobacter, Escherichia, Lactobacillus, Providencia, Rhodococcus, and Staphylococcus. The use of visual analytics methods makes it possible to include additional arsenic-associated protein families in the profiling scheme. Finally, investigations are desired on the arsenic sensing and regulatory systems in members of the Bacteroidetes phylum.