DeepReg: a deep learning hybrid model for predicting transcription factors in eukaryotic and prokaryotic genomes.

Deep learning models (DLMs) have gained importance in predicting, detecting, translating, and classifying a diversity of inputs. In bioinformatics, DLMs have been used to predict protein structures, transcription factor-binding sites, and promoters. In this work, we propose a hybrid model to identify transcription factors (TFs) among prokaryotic and eukaryotic protein sequences, named Deep Regulation (DeepReg) model. Two architectures were used in the DL model: a convolutional neural network (CNN), and a bidirectional long-short-term memory (BiLSTM). DeepReg reached a precision of 0.99, a recall of 0.97, and an F1-score of 0.98. The quality of our predictions, the bias-variance trade-off approach, and the characterization of new TF predictions were evaluated and compared against those produced by DeepTFactor, as well as against experimental data from three model organisms. Predictions based on our DLM tended to exhibit less variance and bias than those from DeepTFactor, thus increasing reliability and decreasing overfitting.

Functional analysis of the AUG initiator codon context reveals novel conserved sequences that disfavor mRNA translation in eukaryotes.

mRNA translation is a fundamental process for life. Selection of the translation initiation site (TIS) is crucial, as it establishes the correct open reading frame for mRNA decoding. Studies in vertebrate mRNAs discovered that a purine at -3 and a G at +4 (where A of the AUG initiator codon is numbered + 1), promote TIS recognition. However, the TIS context in other eukaryotes has been poorly experimentally analyzed. We analyzed in vitro the influence of the -3, -2, -1 and + 4 positions of the TIS context in rabbit, Drosophila, wheat, and yeast. We observed that -3A conferred the best translational efficiency across these species. However, we found variability at the + 4 position for optimal translation. In addition, the Kozak motif that was defined from mammalian cells was only weakly predictive for wheat and essentially non-predictive for yeast. We discovered eight conserved sequences that significantly disfavored translation. Due to the big differences in translational efficiency observed among weak TIS context sequences, we define a novel category that we termed 'barren AUG context sequences (BACS)', which represent sequences disfavoring translation. Analysis of mRNA-ribosomal complexes structures provided insights into the function of BACS. The gene ontology of the BACS-containing mRNAs is presented.

Fast genome-based delimitation of Enterobacterales species.

Average Nucleotide Identity (ANI) is becoming a standard measure for bacterial species delimitation. However, its calculation can take orders of magnitude longer than similarity estimates based on sampling of short nucleotides, compiled into so-called sketches. These estimates are widely used. However, their variable correlation with ANI has suggested that they might not be as accurate. For a where-the-rubber-meets-the-road assessment, we compared two sketching programs, mash and dashing, against ANI, in delimiting species among Esterobacterales genomes. Receiver Operating Characteristic (ROC) analysis found Area Under the Curve (AUC) values of 0.99, almost perfect species discrimination for all three measures. Subsampling to avoid over-represented species reduced these AUC values to 0.92, still highly accurate. Focused tests with ten genera, each represented by more than three species, also showed almost identical results for all methods. Shigella showed the lowest AUC values (0.68), followed by Citrobacter (0.80). All other genera, Dickeya, Enterobacter, Escherichia, Klebsiella, Pectobacterium, Proteus, Providencia and Yersinia, produced AUC values above 0.90. The species delimitation thresholds varied, with species distance ranges in a few genera overlapping the genus ranges of other genera. Mash was able to separate the E. coli + Shigella complex into 25 apparent phylogroups, four of them corresponding, roughly, to the four Shigella species represented in the data. Our results suggest that fast estimates of genome similarity are as good as ANI for species delimitation. Therefore, these estimates might suffice for covering the role of genomic similarity in bacterial taxonomy, and should increase confidence in their use for efficient bacterial identification and clustering, from epidemiological to genome-based detection of potential contaminants in farming and industry settings.

Sequence Similarity among Structural Repeats in the Piezo Family of Mechanosensitive Ion Channels.

Members of the Piezo family of mechanically activated cation channels are involved in multiple physiological processes in higher eukaryotes, including vascular development, cell differentiation, touch perception, hearing, and more, but they are also common in single-celled eukaryotic microorganisms. Mutations in these proteins in humans are associated with a variety of diseases, such as colorectal adenomatous polyposis, dehydrated hereditary stomatocytosis, and hereditary xerocytosis. Available 3D structures for Piezo proteins show nine regions of four transmembrane segments each that have the same fold. Despite the remarkable similarity among the nine characteristic structural repeats in the family, no significant sequence similarity among them has been reported. Using bioinformatics approaches and the Transporter Classification Database (TCDB) as reference, we reliably identified sequence similarity among repeats based on four lines of evidence: (1) hidden Markov model-profile similarities across repeats at the family level, (2) pairwise sequence similarities between different repeats across Piezo homologs, (3) Piezo-specific conserved sequence signatures that consistently identify the same regions across repeats, and (4) conserved residues that maintain the same orientation and location in 3D space.

Comparative analysis of adenylate isopentenyl transferase genes in plant growth-promoting bacteria and plant pathogenic bacteria.

Cytokinin is a major phytohormone that has been used in agriculture as a plant-growth stimulating compound since its initial discovery in the 1960s. Isopentenyl transferase (IPT) is a rate-limiting enzyme for cytokinin biosynthesis, which is produced by plants as well as bacteria including both plant pathogenic species and plant growth-promoting bacteria (PGPB). It has been hypothesized that there may be differences in IPT function between plant pathogens and PGPB. However, a comprehensive comparison of IPT genes between plant pathogenic and PGPB species has not been performed. Here, we performed a global comparison of IPT genes across bacteria, analyzing their DNA sequences, codon usage, phyletic distribution, promoter structure and genomic context. We found that adenylate type IPT genes are highly specific to plant-associated bacteria and subdivide into two major clades: clade A, largely composed of proteobacterial plant pathogens; and clade B, largely composed of actinomycete PGPB species. Besides these phylogenetic differences, we identified several genomic features that suggest differences in IPT regulation between pathogens and PGPB. Pathogen-associated IPTs tended to occur in predicted virulence loci, whereas PGPB-associated IPTs tended to co-occur with other genes involved in cytokinin metabolism and degradation. Pathogen-associated IPTs also showed elevated gene copy numbers, significant deviation in codon usage patterns, and extended promoters, suggesting differences in regulation and activity levels. Our results are consistent with the hypothesis that differences in IPT regulation and activity exist between plant pathogens and PGPB, which determine their effect on plant host phenotypes through the control of cytokinin levels.

Comparative genomic and functional analysis of Arthrobacter sp. UMCV2 reveals the presence of luxR-related genes inducible by the biocompound N, N-dimethylhexadecilamine.

Quorum sensing (QS) is a bacterial cell-cell communication system with genetically regulated mechanisms dependent on cell density. Canonical QS systems in gram-negative bacteria possess an autoinducer synthase (LuxI family) and a transcriptional regulator (LuxR family) that respond to an autoinducer molecule. In Gram-positive bacteria, the LuxR transcriptional regulators "solo" (not associated with a LuxI homolog) may play key roles in intracellular communication. Arthrobacter sp. UMCV2 is an actinobacterium that promotes plant growth by emitting the volatile organic compound N, N-dimethylhexadecylamine (DMHDA). This compound induces iron deficiency, defense responses in plants, and swarming motility in Arthrobacter sp. UMCV2. In this study, the draft genome of this bacterium was assembled and compared with the genomes of type strains of the Arthrobacter genus, finding that it does not belong to any previously described species. Genome explorations also revealed the presence of 16 luxR-related genes, but no luxI homologs were discovered. Eleven of these sequences possess the LuxR characteristic DNA-binding domain with a helix-turn-helix motif and were designated as auto-inducer-related regulators (AirR). Four sequences possessed LuxR analogous domains and were designated as auto-inducer analogous regulators (AiaR). When swarming motility was induced with DMHDA, eight airR genes and two aiaR genes were upregulated. These results indicate that the expression of multiple luxR-related genes is induced in actinobacteria, such as Arthrobacter sp. UMCV2, by the action of the bacterial biocompound DMHDA when QS behavior is produced.

Non-synonymous to synonymous substitutions suggest that orthologs tend to keep their functions, while paralogs are a source of functional novelty.

Orthologs separate after lineages split from each other and paralogs after gene duplications. Thus, orthologs are expected to remain more functionally coherent across lineages, while paralogs have been proposed as a source of new functions. Because protein functional divergence follows from non-synonymous substitutions, we performed an analysis based on the ratio of non-synonymous to synonymous substitutions (dN/dS), as proxy for functional divergence. We used five working definitions of orthology, including reciprocal best hits (RBH), among other definitions based on network analyses and clustering. The results showed that orthologs, by all definitions tested, had values of dN/dS noticeably lower than those of paralogs, suggesting that orthologs generally tend to be more functionally stable than paralogs. The differences in dN/dS ratios remained suggesting the functional stability of orthologs after eliminating gene comparisons with potential problems, such as genes with high codon usage biases, low coverage of either of the aligned sequences, or sequences with very high similarities. Separation by percent identity of the encoded proteins showed that the differences between the dN/dS ratios of orthologs and paralogs were more evident at high sequence identity, less so as identity dropped. The last results suggest that the differences between dN/dS ratios were partially related to differences in protein identity. However, they also suggested that paralogs undergo functional divergence relatively early after duplication. Our analyses indicate that choosing orthologs as probably functionally coherent remains the right approach in comparative genomics.

FastANI, Mash and Dashing equally differentiate between Klebsiella species.

Bacteria of the genus Klebsiella are among the most important multi-drug resistant human pathogens, though they have been isolated from a variety of environments. The importance and ubiquity of these organisms call for quick and accurate methods for their classification. Average Nucleotide Identity (ANI) is becoming a standard for species delimitation based on whole genome sequence comparison. However, much faster genome comparison tools have been appearing in the literature. In this study we tested the quality of different approaches for genome-based species delineation against ANI. To this end, we compared 1,189 Klebsiella genomes using measures calculated with Mash, Dashing, and DNA compositional signatures, all of which run in a fraction of the time required to obtain ANI. Receiver Operating Characteristic (ROC) curve analyses showed equal quality in species discrimination for ANI, Mash and Dashing, with Area Under the Curve (AUC) values above 0.99, followed by DNA signatures (AUC: 0.96). Accordingly, groups obtained at optimized cutoffs largely agree with species designation, with ANI, Mash and Dashing producing 15 species-level groups. DNA signatures broke the dataset into more than 30 groups. Testing Mash to map species after adding draft genomes to the dataset also showed excellent results (AUC above 0.99), producing a total of 26 Klebsiella species-level groups. The ecological niches of Klebsiella strains were found to neither be related to species delimitation, nor to protein functional content, suggesting that a single Klebsiella species can have a wide repertoire of ecological functions.

RegulonDB 11.0: Comprehensive high-throughput datasets on transcriptional regulation in Escherichia coli K-12.

Genomics has set the basis for a variety of methodologies that produce high-throughput datasets identifying the different players that define gene regulation, particularly regulation of transcription initiation and operon organization. These datasets are available in public repositories, such as the Gene Expression Omnibus, or ArrayExpress. However, accessing and navigating such a wealth of data is not straightforward. No resource currently exists that offers all available high and low-throughput data on transcriptional regulation in Escherichia coli K-12 to easily use both as whole datasets, or as individual interactions and regulatory elements. RegulonDB (https://regulondb.ccg.unam.mx) began gathering high-throughput dataset collections in 2009, starting with transcription start sites, then adding ChIP-seq and gSELEX in 2012, with up to 99 different experimental high-throughput datasets available in 2019. In this paper we present a radical upgrade to more than 2000 high-throughput datasets, processed to facilitate their comparison, introducing up-to-date collections of transcription termination sites, transcription units, as well as transcription factor binding interactions derived from ChIP-seq, ChIP-exo, gSELEX and DAP-seq experiments, besides expression profiles derived from RNA-seq experiments. For ChIP-seq experiments we offer both the data as presented by the authors, as well as data uniformly processed in-house, enhancing their comparability, as well as the traceability of the methods and reproducibility of the results. Furthermore, we have expanded the tools available for browsing and visualization across and within datasets. We include comparisons against previously existing knowledge in RegulonDB from classic experiments, a nucleotide-resolution genome viewer, and an interface that enables users to browse datasets by querying their metadata. A particular effort was made to automatically extract detailed experimental growth conditions by implementing an assisted curation strategy applying Natural language processing and machine learning. We provide summaries with the total number of interactions found in each experiment, as well as tools to identify common results among different experiments. This is a long-awaited resource to make use of such wealth of knowledge and advance our understanding of the biology of the model bacterium E. coli K-12.

PathFams: statistical detection of pathogen-associated protein domains.

BACKGROUND: A substantial fraction of genes identified within bacterial genomes encode proteins of unknown function. Identifying which of these proteins represent potential virulence factors, and mapping their key virulence determinants, is a challenging but important goal. RESULTS: To facilitate virulence factor discovery, we performed a comprehensive analysis of 17,929 protein domain families within the Pfam database, and scored them based on their overrepresentation in pathogenic versus non-pathogenic species, taxonomic distribution, relative abundance in metagenomic datasets, and other factors. CONCLUSIONS: We identify pathogen-associated domain families, candidate virulence factors in the human gut, and eukaryotic-like mimicry domains with likely roles in virulence. Furthermore, we provide an interactive database called PathFams to allow users to explore pathogen-associated domains as well as identify pathogen-associated domains and domain architectures in user-uploaded sequences of interest. PathFams is freely available at https://pathfams.uwaterloo.ca .

The Functional Differences between the GroEL Chaperonin of Escherichia coli and the HtpB Chaperonin of Legionella pneumophila Can Be Mapped to Specific Amino Acid Residues.

Group I chaperonins are a highly conserved family of essential proteins that self-assemble into molecular nanoboxes that mediate the folding of cytoplasmic proteins in bacteria and organelles. GroEL, the chaperonin of Escherichia coli, is the archetype of the family. Protein folding-independent functions have been described for numerous chaperonins, including HtpB, the chaperonin of the bacterial pathogen Legionella pneumophila. Several protein folding-independent functions attributed to HtpB are not shared by GroEL, suggesting that differences in the amino acid (aa) sequence between these two proteins could correlate with functional differences. GroEL and HtpB differ in 137 scattered aa positions. Using the Evolutionary Trace (ET) bioinformatics method, site-directed mutagenesis, and a functional reporter test based upon a yeast-two-hybrid interaction with the eukaryotic protein ECM29, it was determined that out of those 137 aa, ten (M68, M212, S236, K298, N507 and the cluster AEHKD in positions 471-475) were involved in the interaction of HtpB with ECM29. GroEL was completely unable to interact with ECM29, but when GroEL was modified at those 10 aa positions, to display the HtpB aa, it acquired a weak ability to interact with ECM29. This constitutes proof of concept that the unique functional abilities of HtpB can be mapped to specific aa positions.

The Transporter Classification Database (TCDB): 2021 update.

The Transporter Classification Database (TCDB; tcdb.org) is a freely accessible reference resource, which provides functional, structural, mechanistic, medical and biotechnological information about transporters from organisms of all types. TCDB is the only transport protein classification database adopted by the International Union of Biochemistry and Molecular Biology (IUBMB) and now (October 1, 2020) consists of 20 653 proteins classified in 15 528 non-redundant transport systems with 1567 tabulated 3D structures, 18 336 reference citations describing 1536 transporter families, of which 26% are members of 82 recognized superfamilies. Overall, this is an increase of over 50% since the last published update of the database in 2016. This comprehensive update of the database contents and features include (i) adoption of a chemical ontology for substrates of transporters, (ii) inclusion of new superfamilies, (iii) a domain-based characterization of transporter families for the identification of new members as well as functional and evolutionary relationships between families, (iv) development of novel software to facilitate curation and use of the database, (v) addition of new subclasses of transport systems including 11 novel types of channels and 3 types of group translocators and (vi) the inclusion of many man-made (artificial) transmembrane pores/channels and carriers.

Progress in quickly finding orthologs as reciprocal best hits: comparing blast, last, diamond and MMseqs2.

BACKGROUND: Finding orthologs remains an important bottleneck in comparative genomics analyses. While the authors of software for the quick comparison of protein sequences evaluate the speed of their software and compare their results against the most usual software for the task, it is not common for them to evaluate their software for more particular uses, such as finding orthologs as reciprocal best hits (RBH). Here we compared RBH results obtained using software that runs faster than blastp. Namely, lastal, diamond, and MMseqs2. RESULTS: We found that lastal required the least time to produce results. However, it yielded fewer results than any other program when comparing the proteins encoded by evolutionarily distant genomes. The program producing the most similar number of RBH to blastp was diamond ran with the "ultra-sensitive" option. However, this option was diamond's slowest, with the "very-sensitive" option offering the best balance between speed and RBH results. The speeding up of the programs was much more evident when dealing with eukaryotic genomes, which code for more numerous proteins. For example, lastal took a median of approx. 1.5% of the blastp time to run with bacterial proteomes and 0.6% with eukaryotic ones, while diamond with the very-sensitive option took 7.4% and 5.2%, respectively. Though estimated error rates were very similar among the RBH obtained with all programs, RBH obtained with MMseqs2 had the lowest error rates among the programs tested. CONCLUSIONS: The fast algorithms for pairwise protein comparison produced results very similar to blast in a fraction of the time, with diamond offering the best compromise in speed, sensitivity and quality, as long as a sensitivity option, other than the default, was chosen.

Expansion of the Transporter-Opsin-G protein-coupled receptor superfamily with five new protein families.

Here we provide bioinformatic evidence that the Organo-Arsenical Exporter (ArsP), Endoplasmic Reticulum Retention Receptor (KDELR), Mitochondrial Pyruvate Carrier (MPC), L-Alanine Exporter (AlaE), and the Lipid-linked Sugar Translocase (LST) protein families are members of the Transporter-Opsin-G Protein-coupled Receptor (TOG) Superfamily. These families share domains homologous to well-established TOG superfamily members, and their topologies of transmembranal segments (TMSs) are compatible with the basic 4-TMS repeat unit characteristic of this Superfamily. These repeat units tend to occur twice in proteins as a result of intragenic duplication events, often with subsequent gain/loss of TMSs in many superfamily members. Transporters within the ArsP family allow microbial pathogens to expel toxic arsenic compounds from the cell. Members of the KDELR family are involved in the selective retrieval of proteins that reside in the endoplasmic reticulum. Proteins of the MPC family are involved in the transport of pyruvate into mitochondria, providing the organelle with a major oxidative fuel. Members of family AlaE excrete L-alanine from the cell. Members of the LST family are involved in the translocation of lipid-linked glucose across the membrane. These five families substantially expand the range of substrates of transport carriers in the superfamily, although KDEL receptors have no known transport function. Clustering of protein sequences reveals the relationships among families, and the resulting tree correlates well with the degrees of sequence similarity documented between families. The analyses and programs developed to detect distant relatedness, provide insights into the structural, functional, and evolutionary relationships that exist between families of the TOG superfamily, and should be of value to many other investigators.

An assessment of genome annotation coverage across the bacterial tree of life.

Although gene-finding in bacterial genomes is relatively straightforward, the automated assignment of gene function is still challenging, resulting in a vast quantity of hypothetical sequences of unknown function. But how prevalent are hypothetical sequences across bacteria, what proportion of genes in different bacterial genomes remain unannotated, and what factors affect annotation completeness? To address these questions, we surveyed over 27 000 bacterial genomes from the Genome Taxonomy Database, and measured genome annotation completeness as a function of annotation method, taxonomy, genome size, 'research bias' and publication date. Our analysis revealed that 52 and 79 % of the average bacterial proteome could be functionally annotated based on protein and domain-based homology searches, respectively. Annotation coverage using protein homology search varied significantly from as low as 14 % in some species to as high as 98 % in others. We found that taxonomy is a major factor influencing annotation completeness, with distinct trends observed across the microbial tree (e.g. the lowest level of completeness was found in the Patescibacteria lineage). Most lineages showed a significant association between genome size and annotation incompleteness, likely reflecting a greater degree of uncharacterized sequences in 'accessory' proteomes than in 'core' proteomes. Finally, research bias, as measured by publication volume, was also an important factor influencing genome annotation completeness, with early model organisms showing high completeness levels relative to other genomes in their own taxonomic lineages. Our work highlights the disparity in annotation coverage across the bacterial tree of life and emphasizes a need for more experimental characterization of accessory proteomes as well as understudied lineages.

The volatile organic compound dimethylhexadecylamine affects bacterial growth and swarming motility of bacteria.

Bacteria have developed different intra- and inter-specific communication mechanisms that involve the production, release, and detection of signaling molecules, because these molecules serve as the autoinducers involved in "quorum sensing" systems. Other communication mechanisms employ volatile signaling molecules that regulate different bacterial processes. The Arthrobacter agilis strain UMCV2 is a plant growth promoting actinobacterium, which induces plant growth and inhibits phytopathogenic fungi by emitting the dimethylhexadecylamine (DMHDA). However, little is known about the effect of this volatile compound on A. agilis UMCV2 itself, as well as on other bacteria. By exposing A. agilis UMCV2 and bacteria of the genus Bacillus and Pseudomonas to different concentrations of DMHDA, this study showed the dose-dependent effects of DMHDA on A. agilis UMCV2 growth, cellular viability, swarming motility, and expression of marker genes of the flagellar apparatus of bacteria. DMHDA was found to also modulate swarming motility of Bacillus sp. ZAP018 and P. fluorescens UM270, but not that of P. aeruginosa PA01. These data indicate that DMHDA is involved in both intra- and inter-specific bacterial interaction.

The predominance of nucleotidyl activation in bacterial phosphonate biosynthesis.

Phosphonates are rare and unusually bioactive natural products. However, most bacterial phosphonate biosynthetic capacity is dedicated to tailoring cell surfaces with molecules like 2-aminoethylphosphonate (AEP). Although phosphoenolpyruvate mutase (Ppm)-catalyzed installation of C-P bonds is known, subsequent phosphonyl tailoring (Pnt) pathway steps remain enigmatic. Here we identify nucleotidyltransferases in over two-thirds of phosphonate biosynthetic gene clusters, including direct fusions to ~60% of Ppm enzymes. We characterize two putative phosphonyl tailoring cytidylyltransferases (PntCs) that prefer AEP over phosphocholine (P-Cho) - a similar substrate used by the related enzyme LicC, which is a virulence factor in Streptococcus pneumoniae. PntC structural analyses reveal steric discrimination against phosphocholine. These findings highlight nucleotidyl activation as a predominant chemical logic in phosphonate biosynthesis and set the stage for probing diverse phosphonyl tailoring pathways.

Aldehyde dehydrogenase diversity in bacteria of the Pseudomonas genus.

Aldehyde dehydrogenases (ALDHs) comprise one of the most ancient protein superfamilies widely distributed in the three domains of life. Their members have been extensively studied in animals and plants, sorted out in different ALDH protein families and their participation in a broad variety of metabolic pathways has been documented. Paradoxically, no systematic studies comprising ALDHs from bacteria have been performed so far. Among bacteria, the genus Pseudomonas occupies numerous ecological niches, and is one of the most complex bacterial genera with the largest number of known species. For these reasons, we selected Pseudomonas as a paradigm to analyze the diversity of ALDHs in bacteria. With this aim, complete Pseudomonas genome sequences and annotations were retrieved from NCBI's RefSeq genome database. The 258 Pseudomonas strains belong to 46 different species, along with 23 with no species designation. The genomes of these Pseudomonas contain from 3,315 to 6,825 annotated protein coding genes. A total of 6,510 ALDH sequences were found in the selected Pseudomonas, with a median of 24 ALDH-coding genes per strain (by comparison humans possess only 19 different ALDH loci). Pseudomonas saudiphocaensis possesses the lowest number of aldh genes (9), while Pseudomonas pseudoalcaligenes KF707 NBRC110670 possesses the maximum number of aldh genes (49). The ALDHs found in Pseudomonas can be sorted out into 42 protein families, with a predominance of 14 families, which contained 76% of all ALDHs found. In this regard, it is important to note that many Pseudomonas genomes have multiple aldh genes coding for proteins belonging to the same family. Given that all strains contained members of families ALDH4, ALDH5, ALDH6, ALDH14, ALDH18 and ALDH27, we consider these families to be part of the core Pseudomonas genome.

Environmentally-driven gene content convergence and the Bacillus phylogeny.

BACKGROUND: Members of the Bacillus genus have been isolated from a variety of environments. However, the relationship between potential metabolism and the niche from which bacteria of this genus have been isolated has not been extensively studied. The existence of a monophyletic aquatic Bacillus group, composed of members isolated from both marine and fresh water has been proposed. Here, we present a phylogenetic/phylogenomic analysis to investigate the potential relationship between the environment from which group members have been isolated and their evolutionary origin. We also carried out hierarchical clustering based on functional content to test for potential environmental effects on the genetic content of these bacteria. RESULTS: The phylogenetic reconstruction showed that Bacillus strains classified as aquatic have evolutionary origins in different lineages. Although we observed the presence of a clade consisting exclusively of aquatic Bacillus, it is not comprised of the same strains previously reported. In contrast to phylogeny, clustering based on the functional categories of the encoded proteomes resulted in groups more compatible with the environments from which the organisms were isolated. This evidence suggests a detectable environmental influence on bacterial genetic content, despite their different evolutionary origins. CONCLUSION: Our results suggest that aquatic Bacillus species have polyphyletic origins, but exhibit convergence at the gene content level.

Bioinformatic characterization of the Anoctamin Superfamily of Ca2+-activated ion channels and lipid scramblases.

Our laboratory has developed bioinformatic strategies for identifying distant phylogenetic relationships and characterizing families and superfamilies of transport proteins. Results using these tools suggest that the Anoctamin Superfamily of cation and anion channels, as well as lipid scramblases, includes three functionally characterized families: the Anoctamin (ANO), Transmembrane Channel (TMC) and Ca2+-permeable Stress-gated Cation Channel (CSC) families; as well as four families of functionally uncharacterized proteins, which we refer to as the Anoctamin-like (ANO-L), Transmembrane Channel-like (TMC-L), and CSC-like (CSC-L1 and CSC-L2) families. We have constructed protein clusters and trees showing the relative relationships among the seven families. Topological analyses suggest that the members of these families have essentially the same topologies. Comparative examination of these homologous families provides insight into possible mechanisms of action, indicates the currently recognized organismal distributions of these proteins, and suggests drug design potential for the disease-related channel proteins.