Global profiling of Shewanella oneidensis MR-1: expression of hypothetical genes and improved functional annotations

Crystal structure of the anti-CRISPR repressor Aca2

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The crystal structure of the anti-CRISPR repressor Aca2 has been solved to 1.34 Å.

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Aca2 contains a new dimerization domain for HTH transcriptional regulators.

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Aca2-like regulators are found encoded in diverse biological contexts.

Bacteria use adaptive CRISPR-Cas immune mechanisms to protect from invasion by bacteriophages and other mobile genetic elements. In response, bacteriophages and mobile genetic elements have co-evolved anti-CRISPR proteins to inhibit the bacterial defense. We and others have previously shown that anti-CRISPR associated (Aca) proteins can regulate this anti-CRISPR counter-attack. Here, we report the first structure of an Aca protein, the Aca2 DNA-binding transcriptional autorepressor from Pectobacterium carotovorum bacteriophage ZF40, determined to 1.34 Å. Aca2 presents a conserved N-terminal helix-turn-helix DNA-binding domain and a previously uncharacterized C-terminal dimerization domain. Dimerization positions the Aca2 recognition helices for insertion into the major grooves of target DNA, supporting its role in regulating anti-CRISPRs. Furthermore, database comparisons identified uncharacterized Aca2 structural homologs in pathogenic bacteria, suggesting that Aca2 represents the first characterized member of a more widespread family of transcriptional regulators.

Flavodoxins as Novel Therapeutic Targets against Helicobacter pylori and Other Gastric Pathogens

Flavodoxins are small soluble electron transfer proteins widely present in bacteria and absent in vertebrates. Flavodoxins participate in different metabolic pathways and, in some bacteria, they have been shown to be essential proteins representing promising therapeutic targets to fight bacterial infections. Using purified flavodoxin and chemical libraries, leads can be identified that block flavodoxin function and act as bactericidal molecules, as it has been demonstrated for Helicobacter pylori (Hp), the most prevalent human gastric pathogen. Increasing antimicrobial resistance by this bacterium has led current therapies to lose effectiveness, so alternative treatments are urgently required. Here, we summarize, with a focus on flavodoxin, opportunities for pharmacological intervention offered by the potential protein targets described for this bacterium and provide information on other gastrointestinal pathogens and also on bacteria from the gut microbiota that contain flavodoxin. The process of discovery and development of novel antimicrobials specific for Hp flavodoxin that is being carried out in our group is explained, as it can be extrapolated to the discovery of inhibitors specific for other gastric pathogens. The high specificity for Hp of the antimicrobials developed may be of help to reduce damage to the gut microbiota and to slow down the development of resistant Hp mutants.

ORCAE-AOCC: A Centralized Portal for the Annotation of African Orphan Crop Genomes

ORCAE (Online Resource for Community Annotation of Eukaryotes) is a public genome annotation curation resource. ORCAE-AOCC is a branch that is dedicated to the genomes published as part of the African Orphan Crops Consortium (AOCC). The motivation behind the development of the ORCAE platform was to create a knowledge-based website where the research-community can make contributions to improve genome annotations. All changes to any given gene-model or gene description are stored, and the entire annotation history can be retrieved. Genomes can either be set to “public” or “restricted” mode; anonymous users can browse public genomes but cannot make any changes. Aside from providing a user- friendly interface to view genome annotations, the platform also includes tools and information (such as gene expression evidence) that enables authorized users to edit and validate genome annotations. The ORCAE-AOCC platform will enable various stakeholders from around the world to coordinate their efforts to annotate and study underutilized crops.

Characterization of a hypothetical protein YVRE from Bacillus subtilis indicates its key role as glucono-lactonase in pentose phosphate pathway and glucose metabolism

Hypothetical proteins are functionally uncharacterized proteins with assigned function using sequence annotation tools. Almost half of the coding regions of several genomes are hypothetical proteins. Therefore, it is of our interest to characterize a hypothetical protein YVRE from the model system Bacillus subtilis using known data. YVRE is assigned the function as a glucono-lactonase using prediction and phylogenetic analysis. A molecular dynamics simulated homology model of YVRE (with calcium) using human senescence marker protein 30 /SMP30 (PDB ID: 3G4E) as template is reported for functional inference. It is observed that the protein possesses bivalent metal binding domain. Molecular docking studies with the substrate glucono-δ-lactone show YVRE binding with the substrate. This data was further validated using cloning and sub-cloning in pUC57 and pET22b+ respectively, followed by expression and purification using nickel affinity chromatography. The activity of YVRE using the substrate glucono-δ-lactone was calculated. The results show the function of YVRE as a gluconolactonase, with higher preference to zinc than calcium or magnesium. Thus, YVRE is shown to play key role in three metabolic pathways namely, pentose phosphate pathway, ascorbate and aldarate metabolism, and caprolactam degradation.

Proteogenomics of rare taxonomic phyla: A prospective treasure trove of protein coding genes

Sustainable innovations in sequencing technologies have resulted in a torrent of microbial genome sequencing projects. However, the prokaryotic genomes sequenced so far are unequally distributed along their phylogenetic tree; few phyla contain the majority, the rest only a few representatives. Accurate genome annotation lags far behind genome sequencing. While automated computational prediction, aided by comparative genomics, remains a popular choice for genome annotation, substantial fraction of these annotations are erroneous. Proteogenomics utilizes protein level experimental observations to annotate protein coding genes on a genome wide scale. Benefits of proteogenomics include discovery and correction of gene annotations regardless of their phylogenetic conservation. This not only allows detection of common, conserved proteins but also the discovery of protein products of rare genes that may be horizontally transferred or taxonomy specific. Chances of encountering such genes are more in rare phyla that comprise a small number of complete genome sequences. We collated all bacterial and archaeal proteogenomic studies carried out to date and reviewed them in the context of genome sequencing projects. Here, we present a comprehensive list of microbial proteogenomic studies, their taxonomic distribution, and also urge for targeted proteogenomics of underexplored taxa to build an extensive reference of protein coding genes.

Binding of Shewanella FadR to the fabA fatty acid biosynthetic gene: implications for contraction of the fad regulon

The Escherichia coli fadR protein product, a paradigm/prototypical FadR regulator, positively regulates fabA and fabB, the two critical genes for unsaturated fatty acid (UFA) biosynthesis. However the scenario in the other Ɣ-proteobacteria, such as Shewanella with the marine origin, is unusual in that Rodionov and coworkers predicted that only fabA (not fabB) has a binding site for FadR protein. It raised the possibility of fad regulon contraction. Here we report that this is the case. Sequence alignment of the FadR homologs revealed that the N-terminal DNA-binding domain exhibited remarkable similarity, whereas the ligand-accepting motif at C-terminus is relatively-less conserved. The FadR homologue of S. oneidensis (referred to FadR_she) was over-expressed and purified to homogeneity. Integrative evidence obtained by FPLC (fast protein liquid chromatography) and chemical cross-linking analyses elucidated that FadR_she protein can dimerize in solution, whose identity was determined by MALDI-TOF-MS. In vitro data from electrophoretic mobility shift assays suggested that FadR_she is almost functionally-exchangeable/equivalent to E. coli FadR (FadR_ec) in the ability of binding the E. coli fabA (and fabB) promoters. In an agreement with that of E. coli fabA, S. oneidensis fabA promoter bound both FadR_she and FadR_ec, and was disassociated specifically with the FadR regulatory protein upon the addition of long-chain acyl-CoA thioesters. To monitor in vivo effect exerted by FadR on Shewanella fabA expression, the native promoter of S. oneidensis fabA was fused to a LacZ reporter gene to engineer a chromosome fabA-lacZ transcriptional fusion in E. coli. As anticipated, the removal of fadR gene gave about 2-fold decrement of Shewanella fabA expression by β-gal activity, which is almost identical to the inhibitory level by the addition of oleate. Therefore, we concluded that fabA is contracted to be the only one member of fad regulon in the context of fatty acid synthesis in the marine bacteria Shewanella genus.

Proteogenomic Analysis of Trichophyton rubrum Aided by RNA Sequencing

Infections caused by dermatophytes, Trichophyton rubrum in particular, are among the most common diseases in humans. In this study, we present a proteogenomic analysis of T. rubrum based on whole-genome proteomics and RNA-Seq studies. We confirmed 4291 expressed proteins in T. rubrum and validated their annotated gene structures based on 35 874 supporting peptides. In addition, we identified 323 novel peptides (not present in the current annotated protein database of T. rubrum) that can be used to enhance current T. rubrum annotations. A total of 104 predicted genes supported by novel peptides were identified, and 127 gene models suggested by the novel peptides that conflicted with existing annotations were manually assigned based on transcriptomic evidence. RNA-Seq confirmed the validity of 95% of the total peptides. Our study provides evidence that confirms and improves the genome annotation of T. rubrum and represents the first survey of T. rubrum genome annotations based on experimental evidence. Additionally, our integrated proteomics and multisourced transcriptomics approach provides stronger evidence for annotation refinement than proteomic data alone, which helps to address the dilemma of one-hit wonders (uncertainties supported by only one peptide).

Cell growth and protein expression of Shewanella oneidensis in biofilms and hydrogel-entrapped cultures

The performance of biofilm-based bioprocesses is difficult to predict and control because of the intrinsic heterogeneous and dynamic properties of microbial biofilms. Biofilm mimics, such as microbial cells entrapped in polymeric scaffolds that are permeable for nutrients, have been proposed to replace real biofilms to achieve long-term robust performance in engineering applications. However, the physiological differences between cells that are physically entrapped in a synthetic polymeric matrix and biofilm cells that are encased in a self-produced polymeric matrix remain unknown. In this study, using Shewanella oneidensis as a model organism and alginate hydrogel as a model synthetic matrix, we compared the cell growth and protein expression in entrapped cultures and biofilms. The hydrogel-entrapped cultures were found to exhibit a growth rate comparable with biofilms. There was no substantial difference in cell viability, surface charge, as well as hydrophobicity between the cells grown in alginate hydrogel and those grown in biofilms. However, the gel-entrapped cultures were found to be physiologically different from biofilms. The gel-entrapped cultures had a higher demand for metabolic energy. The siderophore-mediated iron uptake was repressed in the gel-entrapped cells. The presence of the hydrogel matrix decreased the expression of proteins involved in biofilm formation, while inducing the production of extracellular DNA (eDNA) in the gel-entrapped cultures. These results advance the fundamental understanding of the physiology of hydrogel-entrapped cells, which can lead to more efficient biofilm mimic-based applications.

Functional evolution of PLP-dependent enzymes based on active-site structural similarities

Families of distantly related proteins typically have very low sequence identity, which hinders evolutionary analysis and functional annotation. Slowly evolving features of proteins, such as an active site, are therefore valuable for annotating putative and distantly related proteins. To date, a complete evolutionary analysis of the functional relationship of an entire enzyme family based on active-site structural similarities has not yet been undertaken. Pyridoxal-5'-phosphate (PLP) dependent enzymes are primordial enzymes that diversified in the last universal ancestor. Using the comparison of protein active site structures (CPASS) software and database, we show that the active site structures of PLP-dependent enzymes can be used to infer evolutionary relationships based on functional similarity. The enzymes successfully clustered together based on substrate specificity, function, and three-dimensional-fold. This study demonstrates the value of using active site structures for functional evolutionary analysis and the effectiveness of CPASS.

New insights into Dehalococcoides mccartyi metabolism from a reconstructed metabolic network-based systems-level analysis of D. mccartyi transcriptomes

Organohalide respiration, mediated by Dehalococcoides mccartyi, is a useful bioremediation process that transforms ground water pollutants and known human carcinogens such as trichloroethene and vinyl chloride into benign ethenes. Successful application of this process depends on the fundamental understanding of the respiration and metabolism of D. mccartyi. Reductive dehalogenases, encoded by rdhA genes of these anaerobic bacteria, exclusively catalyze organohalide respiration and drive metabolism. To better elucidate D. mccartyi metabolism and physiology, we analyzed available transcriptomic data for a pure isolate (Dehalococcoides mccartyi strain 195) and a mixed microbial consortium (KB-1) using the previously developed pan-genome-scale reconstructed metabolic network of D. mccartyi. The transcriptomic data, together with available proteomic data helped confirm transcription and expression of the majority genes in D. mccartyi genomes. A composite genome of two highly similar D. mccartyi strains (KB-1 Dhc) from the KB-1 metagenome sequence was constructed, and operon prediction was conducted for this composite genome and other single genomes. This operon analysis, together with the quality threshold clustering analysis of transcriptomic data helped generate experimentally testable hypotheses regarding the function of a number of hypothetical proteins and the poorly understood mechanism of energy conservation in D. mccartyi. We also identified functionally enriched important clusters (13 for strain 195 and 11 for KB-1 Dhc) of co-expressed metabolic genes using information from the reconstructed metabolic network. This analysis highlighted some metabolic genes and processes, including lipid metabolism, energy metabolism, and transport that potentially play important roles in organohalide respiration. Overall, this study shows the importance of an organism's metabolic reconstruction in analyzing various "omics" data to obtain improved understanding of the metabolism and physiology of the organism.

Improving the efficiency of plasmid transformation in Shewanella oneidensis MR-1 by removing ClaI restriction site

Here we demonstrate that elimination of ClaI restriction site from the sequence of a plasmid DNA increases the efficiency of transformation of Shewanella oneidensis MR-1 significantly. To achieve reliable transformation of S. oneidensis MR-1 plasmids either lacking ClaI site or isolated from primary transformants of S. oneidensis should be used.

Single-cell genomics reveals metabolic strategies for microbial growth and survival in an oligotrophic aquifer

Bacteria from the genus Pedobacter are a major component of microbial assemblages at Hanford Site (a largely decommissioned nuclear production complex) in eastern Washington state, USA, and have been shown to change significantly in abundance in response to the subsurface intrusion of Columbia River water. Here we employed single-cell genomics techniques to shed light on the physiological niche of these micro-organisms. Analysis of four Pedobacter single amplified genomes (SAGs) from Hanford Site sediments revealed a chemoheterotrophic lifestyle, with the potential to exist under both aerobic and microaerophilic conditions via expression of both aa3-type and cbb3-type cytochrome c oxidases. These SAGs encoded a wide range of both intra- and extracellular carbohydrate-active enzymes, potentially enabling the degradation of recalcitrant substrates such as xylan and chitin, and the utilization of more labile sugars such as mannose and fucose. Coupled to these enzymes, a diversity of transporters and sugar-binding molecules were involved in the uptake of carbon from the extracellular local environment. The SAGs were enriched in TonB-dependent receptors, which play a key role in uptake of substrates resulting from degradation of recalcitrant carbon. Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)-Cas mechanisms for resisting viral infections were identified in all SAGs. These data demonstrate the potential mechanisms utilized for persistence by heterotrophic micro-organisms in a carbon-limited aquifer, and hint at potential linkages between observed Pedobacter abundance shifts within the 300 Area (in the south-eastern corner of the site) subsurface and biogeochemical shifts associated with Columbia River water intrusion.

Exploring the roles of DNA methylation in the metal-reducing bacterium Shewanella oneidensis MR-1

We performed whole-genome analyses of DNA methylation in Shewanella oneidensis MR-1 to examine its possible role in regulating gene expression and other cellular processes. Single-molecule real-time (SMRT) sequencing revealed extensive methylation of adenine (N6mA) throughout the genome. These methylated bases were located in five sequence motifs, including three novel targets for type I restriction/modification enzymes. The sequence motifs targeted by putative methyltranferases were determined via SMRT sequencing of gene knockout mutants. In addition, we found that S. oneidensis MR-1 cultures grown under various culture conditions displayed different DNA methylation patterns. However, the small number of differentially methylated sites could not be directly linked to the much larger number of differentially expressed genes under these conditions, suggesting that DNA methylation is not a major regulator of gene expression in S. oneidensis MR-1. The enrichment of methylated GATC motifs in the origin of replication indicates that DNA methylation may regulate genome replication in a manner similar to that seen in Escherichia coli. Furthermore, comparative analyses suggest that many Gammaproteobacteria, including all members of the Shewanellaceae family, may also utilize DNA methylation to regulate genome replication.

Impact of Solar Radiation on Gene Expression in Bacteria

Microorganisms often regulate their gene expression at the level of transcription and/or translation in response to solar radiation. In this review, we present the use of both transcriptomics and proteomics to advance knowledge in the field of bacterial response to damaging radiation. Those studies pertain to diverse application areas such as fundamental microbiology, water treatment, microbial ecology and astrobiology. Even though it has been demonstrated that mRNA abundance is not always consistent with the protein regulation, we present here an exhaustive review on how bacteria regulate their gene expression at both transcription and translation levels to enable biomarkers identification and comparison of gene regulation from one bacterial species to another.

Unraveling the Complexities of Life Sciences Data

The life sciences have entered into the realm of big data and data-enabled science, where data can either empower or overwhelm. These data bring the challenges of the 5 Vs of big data: volume, veracity, velocity, variety, and value. Both independently and through our involvement with DELSA Global (Data-Enabled Life Sciences Alliance, DELSAglobal.org), the Kolker Lab ( kolkerlab.org ) is creating partnerships that identify data challenges and solve community needs. We specialize in solutions to complex biological data challenges, as exemplified by the community resource of MOPED (Model Organism Protein Expression Database, MOPED.proteinspire.org ) and the analysis pipeline of SPIRE (Systematic Protein Investigative Research Environment, PROTEINSPIRE.org ). Our collaborative work extends into the computationally intensive tasks of analysis and visualization of millions of protein sequences through innovative implementations of sequence alignment algorithms and creation of the Protein Sequence Universe tool (PSU). Pushing into the future together with our collaborators, our lab is pursuing integration of multi-omics data and exploration of biological pathways, as well as assigning function to proteins and porting solutions to the cloud. Big data have come to the life sciences; discovering the knowledge in the data will bring breakthroughs and benefits.

Proteomics of Pyrococcus furiosus (Pfu): Identification of Extracted Proteins by Three Independent Methods

Pyrococcus furiosus (Pfu) is an excellent organism to generate reference samples for proteomics laboratories because of its moderately sized genome and very little sequence duplication within the genome. We demonstrated a stable and consistent method to prepare proteins in bulk that eliminates growth and preparation as a source of uncertainty in the standard. We performed several proteomic studies in different laboratories using each laboratory's specific workflow as well as separate and integrated data analysis. This study demonstrated that a Pfu whole cell lysate provides suitable protein sample complexity to not only validate proteomic methods, work flows, and benchmark new instruments but also to facilitate comparison of experimental data generated over time and across instruments or laboratories.

Systematic characterization of hypothetical proteins in Synechocystis sp. PCC 6803 reveals proteins functionally relevant to stress responses

We described here a global detection and functional inference of hypothetical proteins involved in stress response in Synechocystis sp. PCC 6803. In the study, we first applied an iTRAQ-LC-MS/MS based quantitative proteomics to the Synechocystis cells grown under five stress conditions. The analysis detected a total of 807 hypothetical proteins with high confidence. Among them, 480 were differentially regulated. We then applied a Weighted Gene Co-expression Network Analysis approach to construct transcriptional networks for Synechocystis under nutrient limitation and osmotic stress conditions using transcriptome datasets. The analysis showed that 305 and 467 coding genes of hypothetical proteins were functionally relevant to nutrient limitation and osmotic stress, respectively. A comparison of responsive hypothetical proteins to all stress conditions allowed identification of 22 hypothetical proteins commonly responsive to all stresses, suggesting they may be part of the core stress responses in Synechocystis. Finally, functional inference of these core stress responsive proteins using both sequence similarity and non-similarity approaches was conducted. The study provided new insights into the stress response networks in Synechocystis, and also demonstrated that a combination of experimental "OMICS" and bioinformatics methodologies could improve functional annotation for hypothetical proteins.

Comparative omics-driven genome annotation refinement: application across Yersiniae

Genome sequencing continues to be a rapidly evolving technology, yet most downstream aspects of genome annotation pipelines remain relatively stable or are even being abandoned. The annotation process is now performed almost exclusively in an automated fashion to balance the large number of sequences generated. One possible way of reducing errors inherent to automated computational annotations is to apply data from omics measurements (i.e. transcriptional and proteomic) to the un-annotated genome with a proteogenomic-based approach. Here, the concept of annotation refinement has been extended to include a comparative assessment of genomes across closely related species. Transcriptomic and proteomic data derived from highly similar pathogenic Yersiniae (Y. pestis CO92, Y. pestis Pestoides F, and Y. pseudotuberculosis PB1/+) was used to demonstrate a comprehensive comparative omic-based annotation methodology. Peptide and oligo measurements experimentally validated the expression of nearly 40% of each strain's predicted proteome and revealed the identification of 28 novel and 68 incorrect (i.e., observed frameshifts, extended start sites, and translated pseudogenes) protein-coding sequences within the three current genome annotations. Gene loss is presumed to play a major role in Y. pestis acquiring its niche as a virulent pathogen, thus the discovery of many translated pseudogenes, including the insertion-ablated argD, underscores a need for functional analyses to investigate hypotheses related to divergence. Refinements included the discovery of a seemingly essential ribosomal protein, several virulence-associated factors, a transcriptional regulator, and many hypothetical proteins that were missed during annotation.

Correlation of macroscopic aggregation behavior and microscopic adhesion properties of bacteria strains using a dimensionless Tabor's parameter

Macroscopic adhesion-aggregation, floc formation, and subsequent transportation of microorganisms in porous media are closely related to the microscopic behavior and properties of individual cells. The classical Tabor's parameter in colloidal science is modified to correlate the macroscopic aggregation and microscopic adhesion properties of microorganisms. Seven bacterial strains relevant to wastewater treatment and bioremediation were characterized in terms of their macroscopic aggregation index (AI) using an optical method, and their microscopic coupled adhesion and deformation properties using atomic force microscopy (AFM). Single cells were indented to measure the range and magnitude of the repulsive-attractive intersurface forces, elastic modulus, thickness and density of the cellular surface substances (CSS). The strong correlation suggests that cost and time effective microscopic AFM characterization is capable of making reliable prediction of macroscopic behavior.

The Response of Shewanella oneidensis MR-1 to Cr(III) Toxicity Differs from that to Cr(VI)

Chromium is a contaminant of concern that is found in drinking water in its soluble, hexavalent form [Cr(VI)] and that is known to be toxic to eukaryotes and prokaryotes. Trivalent chromium [Cr(III)] is thought to be largely harmless due to its low solubility and inability to enter cells. Previous work has suggested that Cr(III) may also be toxic to microorganisms but the mechanism remained elusive. In this work, we probe the toxicity of Cr(III) to Shewanella oneidensis MR-1, a bacterium able to reduce Cr(VI) to Cr(III) and compare it to Cr(VI) toxicity. We found evidence for Cr(III) toxicity both under Cr(VI) reducing conditions, during which Cr(III) was generated by the reduction process, and under non-reducing conditions, when Cr(III) was amended exogenously. Interestingly, cells exposed to Cr(III) (200 μM) experienced rapid viability loss as measured by colony forming units on Luria–Bertani (LB) agar plates. In contrast, they maintained some enzymatic activity and cellular integrity. Cr(VI)-exposed cells exhibited loss of enzymatic activity and cell lysis. The loss of viability of Cr(III)-exposed cells was not due to membrane damage or to enzymatic inhibition but rather appeared to be associated with an abnormal morphology that consisted of chains of membrane-enclosed units of irregular size. Exposure of abnormal cells to growth conditions resulted in membrane damage and cell death, which is consistent with the observed viability loss on LB plates. While Cr(VI) was taken up intracellularly and caused cell lysis, the toxic effect of Cr(III) appeared to be associated with extracellular interactions leading to an ultimately lethal cell morphology.

Proteome driven re-evaluation and functional annotation of the Streptococcus pyogenes SF370 genome

Background

The genome data of Streptococcus pyogenes SF370 has been widely used by many researchers and provides a vast array of interesting findings. Nevertheless, approximately 40% of genes remain classified as hypothetical proteins, and several coding sequences (CDSs) have been unrecognized. In this study, we attempted a shotgun proteomic analysis with a six-frame database that was independent of genome annotation.

Results

Nine proteins encoded by novel ORFs were found by shotgun proteomic analysis, and their specific mRNAs were verified by reverse transcriptional PCR (RT-PCR). We also provided functional annotations for hypothetical genes using proteomic analysis from three different culture conditions that were separated into three fractions: supernatant, soluble, and insoluble. Consequently, we identified 567 proteins on re-evaluation of the proteomic data using an in-house database comprising 1,697 annotated and nine non-annotated CDSs. We provided functional annotations for 126 hypothetical proteins (18.9% out of the 668 hypothetical proteins) based on their cellular fractions and expression profiles under different culture conditions.

Conclusions

The list of amino acid sequences that were annotated by genome analysis contains outdated information and unrecognized protein-coding sequences. We suggest that the six-frame database derived from actual DNA sequences be used for reliable proteomic analysis. In addition, the experimental evidence from functional proteomic analysis is useful for the re-evaluation of previously sequenced genomes.

Shewanella oneidensis MR-1 sensory box protein involved in aerobic and anoxic growth

Although little is known of potential function for conserved signaling proteins, it is hypothesized that such proteins play important roles to coordinate cellular responses to environmental stimuli. In order to elucidate the function of a putative sensory box protein (PAS domains) in Shewanella oneidensis MR-1, the physiological role of SO3389 was characterized. The predicted open reading frame (ORF) encodes a putative sensory box protein that has PAS, GGDEF, and EAL domains, and an in-frame deletion mutant was constructed (ΔSO3389) with approximately 95% of the ORF deleted. Under aerated conditions, wild-type and mutant cultures had similar growth rates, but the mutant culture had a lower growth rate under static, aerobic conditions. Oxygen consumption rates were lower for mutant cultures (1.5-fold), and wild-type cultures also maintained lower dissolved oxygen concentrations under aerated growth conditions. When transferred to anoxic conditions, the mutant did not grow with fumarate, iron(III), or dimethyl sulfoxide (DMSO) as electron acceptors. Biochemical assays demonstrated the expression of different c-type cytochromes as well as decreased fumarate reductase activity in the mutant transferred to anoxic growth conditions. Transcriptomic studies showed the inability of the mutant to up-express and down-express genes, including c-type cytochromes (e.g., SO4047/SO4048, SO3285/SO3286), reductases (e.g., SO0768, SO1427), and potential regulators (e.g., SO1329). The complemented strain was able to grow when transferred from aerobic to anoxic growth conditions with the tested electron acceptors. The modeled structure for the SO3389 PAS domains was highly similar to the crystal structures of FAD-binding PAS domains that are known O2/redox sensors. Based on physiological, genomic, and bioinformatic results, we suggest that the sensory box protein, SO3389, is an O2/redox sensor that is involved in optimization of aerobic growth and transitions to anoxia in S. oneidensis MR-1.

Proteome changes in the initial bacterial colonist during ecological succession in an acid mine drainage biofilm community

Proteomes of acid mine drainage biofilms at different stages of ecological succession were examined to understand microbial responses to changing community membership. We evaluated the degree of reproducibility of the community proteomes between samples of the same growth stage and found stable and predictable protein abundance patterns across time and sampling space, allowing for a set of 50 classifier proteins to be identified for use in predicting growth stages of undefined communities. Additionally, physiological changes in the dominant species, Leptospirillum Group II, were analysed as biofilms mature. During early growth stages, this population responds to abiotic stresses related to growth on the acid mine drainage solution. Enzymes involved in protein synthesis, cell division and utilization of 1- and 2-carbon compounds were more abundant in early growth stages, suggesting rapid growth and a reorganization of metabolism during biofilm initiation. As biofilms thicken and diversify, external stresses arise from competition for dwindling resources, which may inhibit cell division of Leptospirillum Group II through the SOS response. This population also represses translation and synthesizes more complex carbohydrates and amino acids in mature biofilms. These findings provide unprecedented insight into the physiological changes that may result from competitive interactions within communities in natural environments.

SQID: an intensity-incorporated protein identification algorithm for tandem mass spectrometry

To interpret LC-MS/MS data in proteomics, most popular protein identification algorithms primarily use predicted fragment m/z values to assign peptide sequences to fragmentation spectra. The intensity information is often undervalued, because it is not as easy to predict and incorporate into algorithms. Nevertheless, the use of intensity to assist peptide identification is an attractive prospect and can potentially improve the confidence of matches and generate more identifications. On the basis of our previously reported study of fragmentation intensity patterns, we developed a protein identification algorithm, SeQuence IDentfication (SQID), that makes use of the coarse intensity from a statistical analysis. The scoring scheme was validated by comparing with Sequest and X!Tandem using three data sets, and the results indicate an improvement in the number of identified peptides, including unique peptides that are not identified by Sequest or X!Tandem. The software and source code are available under the GNU GPL license at http://quiz2.chem.arizona.edu/wysocki/bioinformatics.htm.

Estimating false discovery rates for peptide and protein identification using randomized databases

MS-based proteomics characterizes protein contents of biological samples. The most common approach is to first match observed MS/MS peptide spectra against theoretical spectra from a protein sequence database and then to score these matches. The false discovery rate (FDR) can be estimated as a function of the score by searching together the protein sequence database and its randomized version and comparing the score distributions of the randomized versus nonrandomized matches. This work introduces a straightforward isotonic regression-based method to estimate the cumulative FDRs and local FDRs (LFDRs) of peptide identification. Our isotonic method not only performed as well as other methods used for comparison, but also has the advantages of being: (i) monotonic in the score, (ii) computationally simple, and (iii) not dependent on assumptions about score distributions. We demonstrate the flexibility of our approach by using it to estimate FDRs and LFDRs for protein identification using summaries of the peptide spectra scores. We reconfirmed that several of these methods were superior to a two-peptide rule. Finally, by estimating both the FDRs and LFDRs, we showed for both peptide and protein identification, moderate FDR values (5%) corresponded to large LFDR values (53 and 60%).

From complete genome sequence to 'complete' understanding?

The rapidly accumulating genome sequence data allow researchers to address fundamental biological questions that were not even asked just a few years ago. A major problem in genomics is the widening gap between the rapid progress in genome sequencing and the comparatively slow progress in the functional characterization of sequenced genomes. Here we discuss two key questions of genome biology: whether we need more genomes, and how deep is our understanding of biology based on genomic analysis. We argue that overly specific annotations of gene functions are often less useful than the more generic, but also more robust, functional assignments based on protein family classification. We also discuss problems in understanding the functions of the remaining 'conserved hypothetical' genes.

Shewanella knowledgebase: integration of the experimental data and computational predictions suggests a biological role for transcription of intergenic regions

Shewanellae are facultative γ-proteobacteria whose remarkable respiratory versatility has resulted in interest in their utility for bioremediation of heavy metals and radionuclides and for energy generation in microbial fuel cells. Extensive experimental efforts over the last several years and the availability of 21 sequenced Shewanella genomes made it possible to collect and integrate a wealth of information on the genus into one public resource providing new avenues for making biological discoveries and for developing a system level understanding of the cellular processes. The Shewanella knowledgebase was established in 2005 to provide a framework for integrated genome-based studies on Shewanella ecophysiology. The present version of the knowledgebase provides access to a diverse set of experimental and genomic data along with tools for curation of genome annotations and visualization and integration of genomic data with experimental data. As a demonstration of the utility of this resource, we examined a single microarray data set from Shewanella oneidensis MR-1 for new insights into regulatory processes. The integrated analysis of the data predicted a new type of bacterial transcriptional regulation involving co-transcription of the intergenic region with the downstream gene and suggested a biological role for co-transcription that likely prevents the binding of a regulator of the upstream gene to the regulator binding site located in the intergenic region.

Database URL:http://shewanella-knowledgebase.org:8080/Shewanella/ or http://spruce.ornl.gov:8080/Shewanella/

Imaging metals in proteins by combining electrophoresis with rapid x-ray fluorescence mapping

Growing evidence points toward a very dynamic role for metals in biology. This suggests that physiological circumstance may mandate metal ion redistribution among ligands. This work addresses a critical need for technology that detects, identifies, and measures the metal-containing components of complex biological matrixes. We describe a direct, user-friendly approach for identifying and quantifying metal-protein adducts in complex samples using native- or SDS-PAGE, blotting, and rapid synchrotron X-ray fluorescence mapping with micro-XANES (X-ray absorption near-edge structure) of entire blots. The identification and quantification of each metal bound to a protein spot has been demonstrated, and the technique has been applied in two exemplary cases. In the first, the speciation of the in vitro binding of exogenous chromium to blood serum proteins was influenced markedly by both the oxidation state of chromium exposed to the serum proteins and the treatment conditions, which is of relevance to the biochemistry of Cr dietary supplements. In the second case, in vivo changes in endogenous metal speciation were examined to probe the influence of oxygen depletion on iron speciation in Shewanella oneidensis.

Complete genome sequence of the electricity-producing "Thermincola potens" strain JR

"Thermincola potens" strain JR is one of the first Gram-positive dissimilatory metal-reducing bacteria (DMRB) for which there is a complete genome sequence. Consistent with the physiology of this organism, preliminary annotation revealed an abundance of multiheme c-type cytochromes that are putatively associated with the periplasm and cell surface in a Gram-positive bacterium. Here we report the complete genome sequence of strain JR.

Complete genome sequence and comparative analysis of Shewanella violacea, a psychrophilic and piezophilic bacterium from deep sea floor sediments

Remineralization of organic matter in deep-sea sediments is important in oceanic biogeochemical cycles, and bacteria play a major role in this process. Shewanella violacea DSS12 is a psychrophilic and piezophilic gamma-proteobacterium that was isolated from the surface layer of deep sea sediment at a depth of 5110 m. Here, we report the complete genome sequence of S. violacea and comparative analysis with the genome of S. oneidensis MR-1, isolated from sediments of a freshwater lake. Unlike S. oneidensis, this deep-sea Shewanella possesses very few terminal reductases for anaerobic respiration and no c-type cytochromes or outer membrane proteins involved in respiratory Fe(iii) reduction, which is characteristic of most Shewanella species. Instead, the S. violacea genome contains more terminal oxidases for aerobic respiration and a much greater number of putative secreted proteases and polysaccharases, in particular, for hydrolysis of collagen, cellulose and chitin, than are encoded in S. oneidensis. Transporters and assimilatory reductases for nitrate and nitrite, and nitric oxide-detoxifying mechanisms (flavohemoglobin and flavorubredoxin) are found in S. violacea. Comparative analysis of the S. violacea genome revealed the respiratory adaptation of this bacterium to aerobiosis, leading to predominantly aerobic oxidation of organic matter in surface sediments, as well as its ability to efficiently use diverse organic matter and to assimilate inorganic nitrogen as a survival strategy in the nutrient-poor deep-sea floor.

Quantifying protein function specificity in the gene ontology

Quantitative or numerical metrics of protein function specificity made possible by the Gene Ontology are useful in that they enable development of distance or similarity measures between protein functions. Here we describe how to calculate four measures of function specificity for GO terms: 1) number of ancestor terms; 2) number of offspring terms; 3) proportion of terms; and 4) Information Content (IC). We discuss the relationship between the metrics and the strengths and weaknesses of each.

Interplay of heritage and habitat in the distribution of bacterial signal transduction systems

Comparative analysis of the complete genome sequences from a variety of poorly studied organisms aims at predicting ecological and behavioral properties of these organisms and helping in characterizing their habitats. This task requires finding appropriate descriptors that could be correlated with the core traits of each system and would allow meaningful comparisons. Using the relatively simple bacterial models, first attempts have been made to introduce suitable metrics to describe the complexity of organism's signaling machinery, which included introducing the "bacterial IQ" score. Here, we use an updated census of prokaryotic signal transduction systems to improve this parameter and evaluate its consistency within selected bacterial phyla. We also introduce a more elaborate descriptor, a set of profiles of relative abundance of members of each family of signal transduction proteins encoded in each genome. We show that these family profiles are well conserved within each genus and are often consistent within families of bacteria. Thus, they reflect evolutionary relationships between organisms as well as individual adaptations of each organism to its specific ecological niche.

Modeling sequence and function similarity between proteins for protein functional annotation

A common task in biological research is to predict function for proteins by comparing sequences between proteins of known and unknown function. This is often done using pair-wise sequence alignment algorithms (e.g. BLAST). A problem with this approach is the assumption of a simple equivalence between a minimum sequence similarity threshold and the function similarity between proteins. This assumption is based on the binary concept of homology in that proteins are or not homologous. The relationship between sequence and function however is more complex as well as pertinent for predicting protein function, e.g. evaluating BLAST alignments or developing training sets for profile models based on functional rather than homologous groupings. Our motivation for this study was to model sequence and function similarity between proteins to gain insights into the "sequence-function similarity relationship between proteins for predicting function. Using our model we found that function similarity generally increases with sequence similarity but with a high degree of variability. This result has implications for pair-wise approaches in that it appears sequence similarity must be very high to ensure high function similarity. Profile models which enable higher sensitivity are a potential solution. However, multiple sequences alignments (a necessary prerequisite) are a problem in that current algorithms have difficulty aligning sequences with very low sequence similarity, which is common in our data set, or are intractable for high numbers of sequences. Given the importance of predicting protein function and the need for multiple sequence alignments, algorithms for accomplishing this task should be further refined and developed.

A statistical model of protein sequence similarity and function similarity reveals overly-specific function predictions

Background

Predicting protein function from primary sequence is an important open problem in modern biology. Not only are there many thousands of proteins of unknown function, current approaches for predicting function must be improved upon. One problem in particular is overly-specific function predictions which we address here with a new statistical model of the relationship between protein sequence similarity and protein function similarity.

Methodology

Our statistical model is based on sets of proteins with experimentally validated functions and numeric measures of function specificity and function similarity derived from the Gene Ontology. The model predicts the similarity of function between two proteins given their amino acid sequence similarity measured by statistics from the BLAST sequence alignment algorithm. A novel aspect of our model is that it predicts the degree of function similarity shared between two proteins over a continuous range of sequence similarity, facilitating prediction of function with an appropriate level of specificity.

Significance

Our model shows nearly exact function similarity for proteins with high sequence similarity (bit score >244.7, e-value >1e⁻⁶², non-redundant NCBI protein database (NRDB)) and only small likelihood of specific function match for proteins with low sequence similarity (bit score <54.6, e-value <1e⁻⁰⁵, NRDB). For sequence similarity ranges in between our annotation model shows an increasing relationship between function similarity and sequence similarity, but with considerable variability. We applied the model to a large set of proteins of unknown function, and predicted functions for thousands of these proteins ranging from general to very specific. We also applied the model to a data set of proteins with previously assigned, specific functions that were electronically based. We show that, on average, these prior function predictions are more specific (quite possibly overly-specific) compared to predictions from our model that is based on proteins with experimentally determined function.

Impact of phenolic substrate and growth temperature on the Arthrobacter chlorophenolicus proteome

We compared the Arthrobacter chlorophenolicus proteome during growth on 4-chlorophenol, 4-nitrophenol, or phenol at 5 and 28 degrees C, both for the wild-type and a mutant strain with mass spectrometry based proteomics. A label-free workflow employing spectral counting identified 3749 proteins across all growth conditions, representing over 70% of the predicted genome and 739 of these proteins form the core proteome. Statistically significant differences were found in the proteomes of cells grown under different conditions including differentiation of hundreds of unknown proteins. The 4-chlorophenol-degradation pathway was confirmed, but not that for phenol.

Proteogenomic monitoring of Geobacter physiology during stimulated uranium bioremediation

Implementation of uranium bioremediation requires methods for monitoring the membership and activities of the subsurface microbial communities that are responsible for reduction of soluble U(VI) to insoluble U(IV). Here, we report a proteomics-based approach for simultaneously documenting the strain membership and microbial physiology of the dominant Geobacter community members during in situ acetate amendment of the U-contaminated Rifle, CO, aquifer. Three planktonic Geobacter-dominated samples were obtained from two wells down-gradient of acetate addition. Over 2,500 proteins from each of these samples were identified by matching liquid chromatography-tandem mass spectrometry spectra to peptides predicted from seven isolate Geobacter genomes. Genome-specific peptides indicate early proliferation of multiple M21 and Geobacter bemidjiensis-like strains and later possible emergence of M21 and G. bemidjiensis-like strains more closely related to Geobacter lovleyi. Throughout biostimulation, the proteome is dominated by enzymes that convert acetate to acetyl-coenzyme A and pyruvate for central metabolism, while abundant peptides matching tricarboxylic acid cycle proteins and ATP synthase subunits were also detected, indicating the importance of energy generation during the period of rapid growth following the start of biostimulation. Evolving Geobacter strain composition may be linked to changes in protein abundance over the course of biostimulation and may reflect changes in metabolic functioning. Thus, metagenomics-independent community proteogenomics can be used to diagnose the status of the subsurface consortia upon which remediation biotechnology relies.

Expansion mechanisms and functional annotations of hypothetical genes in the rice genome

In each completely sequenced genome, 30% to 50% of genes are annotated as uncharacterized hypothetical genes. In the rice (Oryza sativa) genome, 10,918 hypothetical genes were annotated in the latest version (release 6) of the Michigan State University rice genome annotation. We have implemented an integrative approach to analyze their duplication/expansion and function. The analyses show that tandem/segmental duplication and transposition/retrotransposition have significantly contributed to the expansion of hypothetical genes despite their different contribution rates. A total of 3,769 hypothetical genes have been detected from retrogene, tandem, segmental, Pack-MULE, or long terminated direct repeat-related duplication/expansion. The nonsynonymous substitutions per site and synonymous substitutions per site analyses showed that 21.65% of them were still functional, accounting for 7.47% of total hypothetical genes. Global expression analyses have identified 1,672 expressed hypothetical genes. Among them, 415 genes might function in a developmental stage-specific manner. Antisense strand expression and small RNA analyses have demonstrated that a high percentage of these hypothetical genes might play important roles in negatively regulating gene expression. Homologous searches against Arabidopsis (Arabidopsis thaliana), maize (Zea mays), sorghum (Sorghum bicolor), and indica rice genomes suggest that most of the hypothetical genes could be annotated from recently evolved genomic sequences. These data advance the understanding of rice hypothetical genes as being involved in lineage-specific expansion and that they function in a specific developmental stage. Our analyses also provide a valuable means to facilitate the characterization and functional annotation of hypothetical genes in other organisms.

Alliance of proteomics and genomics to unravel the specificities of Sahara bacterium Deinococcus deserti

To better understand adaptation to harsh conditions encountered in hot arid deserts, we report the first complete genome sequence and proteome analysis of a bacterium, Deinococcus deserti VCD115, isolated from Sahara surface sand. Its genome consists of a 2.8-Mb chromosome and three large plasmids of 324 kb, 314 kb, and 396 kb. Accurate primary genome annotation of its 3,455 genes was guided by extensive proteome shotgun analysis. From the large corpus of MS/MS spectra recorded, 1,348 proteins were uncovered and semiquantified by spectral counting. Among the highly detected proteins are several orphans and Deinococcus-specific proteins of unknown function. The alliance of proteomics and genomics high-throughput techniques allowed identification of 15 unpredicted genes and, surprisingly, reversal of incorrectly predicted orientation of 11 genes. Reversal of orientation of two Deinococcus-specific radiation-induced genes, ddrC and ddrH, and identification in D. deserti of supplementary genes involved in manganese import extend our knowledge of the radiotolerance toolbox of Deinococcaceae. Additional genes involved in nutrient import and in DNA repair (i.e., two extra recA, three translesion DNA polymerases, a photolyase) were also identified and found to be expressed under standard growth conditions, and, for these DNA repair genes, after exposure of the cells to UV. The supplementary nutrient import and DNA repair genes are likely important for survival and adaptation of D. deserti to its nutrient-poor, dry, and UV-exposed extreme environment.

D. deserti belongs to the Deinococcaceae, a family of bacteria characterized by an exceptional ability to withstand the lethal effects of DNA-damaging agents, including ionizing radiation, UV light, and desiccation. It was isolated from Sahara surface sands, an extreme and nutrient-poor environment, regularly exposed to intense UV radiation, cycles of extreme temperatures, and desiccation. The evolution of organisms that are able to survive acute irradiation doses of 15,000 Gy is difficult to explain given the apparent absence of highly radioactive habitats on Earth over geologic time. Thus, it seems more likely that the natural selection pressure for the evolution of radiation-resistant bacteria was chronic exposure to nonradioactive forms of DNA damage, in particular those promoted by desiccation. Here, we report the first complete genome sequence of a bacterium, D. deserti VCD115, isolated from hot, arid desert surface sand. Accurate genome annotation of its 3,455 genes was guided by extensive proteome analysis in which 1,348 proteins were uncovered after growth in standard conditions. Supplementary genes involved in manganese import, in nutrient import, and in DNA repair were identified and are likely important for survival and adaptation of D. deserti to its hostile environment.

Expression profiling of hypothetical genes in Desulfovibrio vulgaris leads to improved functional annotation

Hypothetical (HyP) and conserved HyP genes account for >30% of sequenced bacterial genomes. For the sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough, 347 of the 3634 genes were annotated as conserved HyP (9.5%) along with 887 HyP genes (24.4%). Given the large fraction of the genome, it is plausible that some of these genes serve critical cellular roles. The study goals were to determine which genes were expressed and provide a more functionally based annotation. To accomplish this, expression profiles of 1234 HyP and conserved genes were used from transcriptomic datasets of 11 environmental stresses, complemented with shotgun LC–MS/MS and AMT tag proteomic data. Genes were divided into putatively polycistronic operons and those predicted to be monocistronic, then classified by basal expression levels and grouped according to changes in expression for one or multiple stresses. One thousand two hundred and twelve of these genes were transcribed with 786 producing detectable proteins. There was no evidence for expression of 17 predicted genes. Except for the latter, monocistronic gene annotation was expanded using the above criteria along with matching Clusters of Orthologous Groups. Polycistronic genes were annotated in the same manner with inferences from their proximity to more confidently annotated genes. Two targeted deletion mutants were used as test cases to determine the relevance of the inferred functional annotations.

Environmental proteomics: applications of proteome profiling in environmental microbiology and biotechnology

In this review, we present the use of proteomics to advance knowledge in the field of environmental biotechnology, including studies of bacterial physiology, metabolism and ecology. Bacteria are widely applied in environmental biotechnology for their ability to catalyze dehalogenation, methanogenesis, denitrification and sulfate reduction, among others. Their tolerance to radiation and toxic compounds is also of importance. Proteomics has an important role in helping uncover the pathways behind these cellular processes. Environmental samples are often highly complex, which makes proteome studies in this field especially challenging. Some of these challenges are the lack of genome sequences for the vast majority of environmental bacteria, difficulties in isolating bacteria and proteins from certain environments, and the presence of complex microbial communities. Despite these challenges, proteomics offers a unique dynamic view into cellular function. We present examples of environmental proteomics of model organisms, and then discuss metaproteomics (microbial community proteomics), which has the potential to provide insights into the function of a community without isolating organisms. Finally, the environmental proteomics literature is summarized as it pertains to the specific application areas of wastewater treatment, metabolic engineering, microbial ecology and environmental stress responses.