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Here, we report the draft genome sequence of Bacillus cereus strain THSB-6-2, which was isolated from cyanobacterial blooms in Lake Taihu, China. The 5,496,658-bp genome assembly of Bacillus cereus consists of 28 contigs, with a GC content of 35% and with 5,587 protein-coding sequences and 58 RNA genes.

Urine excretory proteins are among the most commonly used biomarkers in body fluids. Computational identification of urine excretory proteins can provide very useful information for identifying targeted disease biomarkers in urine by linking transcriptome or proteomics data. There are few methods based on conventional machine learning algorithms for predicting urine excretory proteins, and most of these methods strongly depend on the extraction of features from urine excretory proteins. An end-to-end model for urine excretory protein prediction, called DeepUEP, is presented using deep neural networks relying on only amino acid sequence information. The model achieves good performance and outperforms existing methods on training and testing sets. By comparing known urinary protein biomarkers with the results of the model, we find that the model can achieve a true-positive rate of over 80% for urinary protein biomarkers that have been detected in more than one study. We also combine our model with transcriptome and proteomics data from lung cancer patients to predict the potential urinary protein biomarkers of lung cancer. A web server is developed for the prediction of urine excretory proteins, and it can be accessed at the following URL: http://www.csbg-jlu.info/DeepUEP/. We believe that our prediction model and web server are useful for biomedical researchers who are interested in identifying urinary protein biomarkers, especially for candidate proteins in transcriptome or proteomics analyses of diseased tissues.

This study assessed the effects of changes in organic carbon content on soil bacterial community composition and diversity in the Antarctic Fildes Peninsula. 16S rRNA gene sequencing was performed to investigate bacterial community composition. Firstly, we found that organic carbon (OrC) and nutrients showed an increasing trend in the lake area. Secondly, soil geochemistry changes affected microbial composition in the soil. Specifically, we found 3416 operational taxonomical units (OTUs) in 300 genera in five main phyla: Proteobacteria, Actinobacteria, Acidobacteria, Chloroflexi, and Bacteroidetes. Although the diversity was similar among the four sites, the composition was different. Among them, Hungateii content changed very significantly, from 16.67% to 33.33%. Canonical correspondence analysis showed that most measured geochemical factors were relevant in structuring microbiomes, and organic carbon concentration showed the highest correlation, followed by NO3−-N. Hungateii was significantly correlated with the content of organic carbon. Our finding suggested organic carbon played an important role in soil bacterial communities of the Antarctic coastal lake region.

Cyanobacterial harmful algal blooms (CyanoHABs) arise as cyanobacteria dominate phytoplankton communities when nutrient levels increase from oligotrophic state. From a wholistic perspective, this longstanding altered phytoplankton structure results from two conditions: one sufficient condition that cyanobacteria can grow maximally with elevated nutrients; one necessary condition that co-living algae cannot grow fast or dominate at the same levels. The sufficient condition, the ‘special’ mechanism of CyanoHABs at the population level, has been established as the synergistic interaction between superior cyanobacterial ecophysiology and elevated nutrients. But it is unknown how these functions arise or whether they are under directed evolution to water eutrophication. The necessary condition, the ‘general’ mechanism of CyanoHABs at the community level, is little understood: why co-living algae cannot form blooms as cyanobacteria? Literature and bioinformatics analyses show that the superior ecophysiology undergoes no directed positive evolution to worldwide eutrophication in general or any local eutrophic waters in particular; instead, these functions are under strong purifying selection and likely acquired through early adaptive radiation in nutrient-deficient conditions, as functions enabling extant cyanobacteria to occupy other niches. The general mechanism turns out to be quite straightforward: cyanobacteria are simple life forms and thus have lower per capita nutrient demand for growth, compared to co-existing eukaryotic algae in cell size and structure, genome size, size of genome-scale metabolic networks, cell content, nutrient requirement. Lower nutrient demand is proved by existing field nutrient supplementation. Both the special and general mechanisms of CyanoHABs are tentative frameworks awaiting further theoretic improvement and empirical assessment.

Cyanobacterial blooms are intensifying global ecological hazards. The fine structure and dynamics of bloom community are critical to understanding bloom development but little understood. Here, the questions whether dominant bloomers have high diversity and whether dominant OTUs (operational taxonomical units) compete with one another were addressed. 16S rRNA gene amplicons from an annual bloom at five locations in Harsha Lake (Ohio, USA) showed cyanobacteria were the dominant phylum, and co-existing major bacterial phyla included Proteobacteria, Bacteroidetes, Actinoacteria, and Verrucomicrobia. On the genus level, the initial dominance by Dolichospermum in June yielded to Planktothrix in July, which were replaced by Microcystis and Cylindrospermopsis in August throughout the bloom. Based on the number of verified unique OTUs (a within-genus biodiversity metric), dominant genera tended to have high within-genus diversity. For example, Dolichospermum had 57 unique OTUs, Planktothrix had 36, Microcystis had 12, and Cylindrospermopsis had 4 unique OTUs. Interestingly, these different OTUs showed different dynamics and association with other OTUs. First, no between-OTU competitions were observed during the bloom cycle, and dominant OTUs were abundant throughout the bloom. Such biodiversity of OTUs and their dynamics were verified in Microcystis aeruginosa with two microcystin synthetase genes (mcyA and mcyG): the relative abundance of both genes varied during the bloom based on quantitative PCR. Two Dolichospermum circinale OTUs and one P. rubescens OTU were most abundant and persistently present throughout the entire bloom. Second, these OTUs differed in the OTUs they were associated with. Third, these OTUs tended to have different levels of association with the environmental factors, even they belonged to the same genera. These findings suggest the structure and dynamics of a cyanobacterial bloom community is complex, with only few OTUs dominating the bloom. Thus, high-resolution molecular characterization will be necessary to understand bloom development.

Lakes of meltwater in the Artic have become one of the transforming landscape changes under global warming. We herein compared microbial communities between sediments and bank soils at an arctic lake post land submergence using geochemistry, 16S rRNA amplicons, and metagenomes. The results obtained showed that each sample had approximately 2,609 OTUs on average and shared 1,716 OTUs based on the 16S rRNA gene V3-V4 region. Dominant phyla in sediments and soils included Proteobacteria, Acidobacteria, Actinobacteria, Gemmatimonadetes, and Nitrospirae; sediments contained a unique phylum, Euryarchaeota, with the phylum Thaumarchaeota being primarily present in bank soils. Among the top 35 genera across all sites, 17 were more abundant in sediments, while the remaining 18 were more abundant in bank soils; seven out of the top ten genera across all sites were only from sediments. A redundancy analysis separated sediment samples from soil samples based on the components of nitrite and ammonium. Metagenome results supported the role of nitrite because most of the genes for denitrification and methane metabolic genes were more abundant in sediments than in soils, while the abundance of phosphorus-utilizing genes was similar and, thus, was not a significant explanatory factor. We identified several modules from the global networks of OTUs that were closely related to some geochemical factors, such as pH and nitrite. Collectively, the present results showing consistent changes in geochemistry, microbiome compositions, and functional genes suggest an ecological mechanism across molecular and community levels that structures microbiomes post land submergence.

The effectiveness of UV-C towards the toxin and odor of M. aeruginosa at population and single cell levels were investigated in three ways. In the absence of UV-C, MC-LR and β-cyclocitral production show similar pattern of incremental rate with growth rate on population level shown as intracellular concentrations of MC-LR (CMC) and β-cyclocitral (CBCC), but the cellular quota of MC-LR (QMC) and β-cyclocitral (QBCC) at single-cell level reached the maximum values, 37.5 ± 1.2 fg cell−1 and 4.3 ± 0.1 fg cell−1, just after the early exponential phase. Second, upon UV-C irradiation, the CMC consistently decreased by 10–41% with increase of UV-C dosage (50–200 mJ cm-2) while CBCC increased by 2–14%. Third, during the 14 days’ post-UV incubation, UV-C at 75–200 mJ cm-2 induced remarkable suppressing effects on both CMC and CBCC for 3–14 days. The suppressing effects on QMC and QBCC were induced by UV-C at 100 mJ cm-2 and above, with shorter suppressing periods by 1–4 days and lower decremental rates by 21%–30% than that of CMC and CBCC, indicating interruptions on biosynthesis processes partially contribute to suppression effects of CMC and CBCC. The suppression effect on either CBCC or QBCC, with higher decrement rates while lower recovery rates, was more severe than CMC and QMC.

CyanoPATH is a database that curates and analyzes the common genomic functional repertoire for cyanobacteria harmful algal blooms (CyanoHABs) in eutrophic waters. Based on the literature of empirical studies and genome/protein databases, it summarizes four types of information: common biological functions (pathways) driving CyanoHABs, customized pathway maps, classification of blooming type based on databases and the genomes of cyanobacteria. A total of 19 pathways are reconstructed, which are involved in the utilization of macronutrients (e.g. carbon, nitrogen, phosphorus and sulfur), micronutrients (e.g. zinc, magnesium, iron, etc.) and other resources (e.g. light and vitamins) and in stress resistance (e.g. lead and copper). These pathways, comprised of both transport and biochemical reactions, are reconstructed with proteins from NCBI and reactions from KEGG and visualized with self-created transport/reaction maps. The pathways are hierarchical and consist of subpathways, protein/enzyme complexes and constituent proteins. New cyanobacterial genomes can be annotated and visualized for these pathways and compared with existing species. This set of genomic functional repertoire is useful in analyzing aquatic metagenomes and metatranscriptomes in CyanoHAB research. Most importantly, it establishes a link between genome and ecology. All these reference proteins, pathways and maps and genomes are free to download at http://www.csbg-jlu.info/CyanoPATH.

Background Compared with disease biomarkers in blood and urine, biomarkers in saliva have distinct advantages in clinical tests, as they can be conveniently examined through noninvasive sample collection. Therefore, identifying human saliva-secretory proteins and further detecting protein biomarkers in saliva have significant value in clinical medicine. There are only a few methods for predicting saliva-secretory proteins based on conventional machine learning algorithms, and all are highly dependent on annotated protein features. Unlike conventional machine learning algorithms, deep learning algorithms can automatically learn feature representations from input data and thus hold promise for predicting saliva-secretory proteins. Results We present a novel end-to-end deep learning model based on multilane capsule network (CapsNet) with differently sized convolution kernels to identify saliva-secretory proteins only from sequence information. The proposed model CapsNet-SSP outperforms existing methods based on conventional machine learning algorithms. Furthermore, the model performs better than other state-of-the-art deep learning architectures mostly used to analyze biological sequences. In addition, we further validate the effectiveness of CapsNet-SSP by comparison with human saliva-secretory proteins from existing studies and known salivary protein biomarkers of cancer. Conclusions The main contributions of this study are as follows: (1) an end-to-end model based on CapsNet is proposed to identify saliva-secretory proteins from the sequence information; (2) the proposed model achieves better performance and outperforms existing models; and (3) the saliva-secretory proteins predicted by our model are statistically significant compared with existing cancer biomarkers in saliva. In addition, a web server of CapsNet-SSP is developed for saliva-secretory protein identification, and it can be accessed at the following URL: http://www.csbg-jlu.info/CapsNet-SSP/. We believe that our model and web server will be useful for biomedical researchers who are interested in finding salivary protein biomarkers, especially when they have identified candidate proteins for analyzing diseased tissues near or distal to salivary glands using transcriptome or proteomics.

We pragmatically delineate the trait repertoire that enables organismal niche specialization. We based our approach on the tenet, derived from evolutionary and complex-system considerations, that genomic units that can significantly contribute to fitness in a certain habitat will be comparatively more complex in organisms specialized to that habitat than their genomic homologs found in organisms from other habitats. We tested this in cyanobacteria forming harmful water blooms, for which decades-long efforts in ecological physiology and genomics exist. Our results essentially confirm that genomics and ecology can be linked through comparative complexity analyses, providing a tool that should be of general applicability for any group of organisms and any habitat, and enabling the posing of grounded hypotheses regarding the ecogenomic basis for diversification., Water bloom development due to eutrophication constitutes a case of niche specialization among planktonic cyanobacteria, but the genomic repertoire allowing bloom formation in only some species has not been fully characterized. We posited that the habitat relevance of a trait begets its underlying genomic complexity, so that traits within the repertoire would be differentially more complex in species successfully thriving in that habitat than in close species that cannot. To test this for the case of bloom-forming cyanobacteria, we curated 17 potentially relevant query metabolic pathways and five core pathways selected according to existing ecophysiological literature. The available 113 genomes were split into those of blooming (45) or nonblooming (68) strains, and an index of genomic complexity for each strain’s version of each pathway was derived. We show that strain versions of all query pathways were significantly more complex in bloomers, with complexity in fact correlating positively with strain blooming incidence in 14 of those pathways. Five core pathways, relevant everywhere, showed no differential complexity or correlations. Gas vesicle, toxin and fatty acid synthesis, amino acid uptake, and C, N, and S acquisition systems were most strikingly relevant in the blooming repertoire. Further, we validated our findings using metagenomic gene expression analyses of blooming and nonblooming cyanobacteria in natural settings, where pathways in the repertoire were differentially overexpressed according to their relative complexity in bloomers, but not in nonbloomers. We expect that this approach may find applications to other habitats and organismal groups.

MotivationTaxonomic analysis of microbiomes based on 16S rRNA amplicons has so far been usually restricted to abundance analysis of operational taxonomic units (OTUs), which are usually mapped to genus, as the furthest level for a balance between accuracy and speed. Biodiversity within taxa has been little studied, due to lack of proper computational tools. Within-taxon diversity reflects genetic polymorphism within the taxa to reveal whether there are potentially more variants/lineages for some microbiome-associated traits, e.g., diseases or bioconversion efficiency. The diversity will aid diagnosis decisions.ResultsHere we introduce a tool, WITOD, for the WIthin-Taxon Operational taxonomic unit Diversity analysis. WITOD works on the alignment of all the OTU sequences within a taxon to get a non-redundant alignment with consensus regions on both ends (due to the conservation of the 16S regions used). Then the relative abundance of identical OTUs is combined; more specific taxonomy is obtained through BLASTn of these OTU sequences against the Silva database. One of the outputs is an OTU table with these unique OTUs with new taxonomy, combined relative abundance. In addition, another table can be constructed which we call the diversity table that associates the number of OTUs for a specific Taxa and the relative abundance in that environment. This can be used to further discover the importance of differing diversity in a given environment.ConclusionsIn this paper, we have introduced a python program WITOD which is a computational tool to analyze the within-taxon biodiversity of microbiome composition. It will be useful in revealing the genetic polymorphism in general and aiding identifying the causative human pathogens or environmental disease vectors. WITOD is available at https://github.com/johncava/WITOD

Genome-scale metabolic networks (GSMs) are mathematic representation of a set of stoichiometrically balanced reactions. However, such static GSMs do not reflect or incorporate functional organization of genes and their dynamic regulation (e.g., operons and regulons). Specifically, there are numerous topologically coupled local reactions through which fluxes are coordinated; and downstream metabolites often dynamically regulate the gene expression of their reactions via feedback. Here, we present a method which reconstructs GSMs with locally coupled reactions and transcriptional regulation of metabolism by key metabolites. The proposed method has outstanding performance in phenotype prediction of wild-type and mutants in Escherichia coli (E. coli), Saccharomyces cerevisiae (S. cerevisiae) and Bacillus subtilis (B. subtilis) growing in various conditions, outperforming existing methods. The predicted growth rate and metabolic fluxes are highly correlated with those experimentally measured. More importantly, our method can also explain the observed growth rates by capturing the ‘real’ (experimentally measured) changes in flux between the wild-types and mutants. Overall, by identifying and incorporating locally organized and regulated functional modules into GSMs, Decrem achieves accurate predictions of phenotypes and has broad applications in bioengineering, synthetic biology and microbial pathology.

Cyanobacterial harmful algal blooms (CyanoHABs) have been found to transmit from N2 fixer-dominated to non-N2 fixer-dominated in many freshwater environments when the supply of N decreases. To elucidate the mechanisms underlying such "counter-intuitive" CyanoHAB species succession, metatranscriptomes (biotic data) and water quality-related variables (abiotic data) were analyzed weekly during a bloom season in Harsha Lake, a multipurpose lake that serves as a drinking water source and recreational ground. Our results showed that CyanoHABs in Harsha Lake started with N2-fixing Anabaena in June (ANA stage) when N was high, and transitioned to non-N2-fixing Microcystis- and Planktothrix-dominated in July (MIC-PLA stage) when N became limited (low TN/TP). Meanwhile, the concentrations of cyanotoxins, i.e., microcystins were significantly higher in the MIC-PLA stage. Water quality results revealed that N species (i.e., TN, TN/TP) and water temperature were significantly correlated with cyanobacterial biomass. Expression levels of several C- and N-processing-related cyanobacterial genes were highly predictive of the biomass of their species. More importantly, the biomasses of Microcystis and Planktothrix were also significantly associated with expressions of microbial genes (mostly from heterotrophic bacteria) related to processing organic substrates (alkaline phosphatase, peptidase, carbohydrate-active enzymes) and cyanophage genes. Collectively, our results suggest that besides environmental conditions and inherent traits of specific cyanobacterial species, the development and succession of CyanoHABs are regulated by co-occurring microorganisms. Specifically, the co-occurring microorganisms can alleviate the nutrient limitation of cyanobacteria by remineralizing organic compounds.

The rapid accumulation of fully sequenced prokaryotic genomes provides unprecedented information for biological studies of bacterial and archaeal organisms in a systematic manner. Operons are the basic functional units for conducting such studies. Here, we review an operon database DOOR (the Database of prOkaryotic OpeRons) that we have previously developed and continue to update. Currently, the database contains 6 975 454 computationally predicted operons in 2072 complete genomes. In addition, the database also contains the following information: (i) transcriptional units for 24 genomes derived using publicly available transcriptomic data; (ii) orthologous gene mapping across genomes; (iii) 6408 cis-regulatory motifs for transcriptional factors of some operons for 203 genomes; (iv) 3 456 718 Rho-independent terminators for 2072 genomes; as well as (v) a suite of tools in support of applications of the predicted operons. In this review, we will explain how such data are computationally derived and demonstrate how they can be used to derive a wide range of higher-level information needed for systems biology studies to tackle complex and fundamental biology questions.

The global expansion and intensification of toxic cyanobacterial blooms require effective algaecides. Algaecides should be selective, effective, fast-acting, and ideally suppress cyanotoxin production. In this study, whether both maximum growth suppression and minimal toxin production can be simultaneously achieved was tested with a selective algaecide H2O2, through its ability to induce apoptosis-like programmed cell death (AL PCD) in a common bloom species Microcystis aeruginosa. Under doses of 1−15 mg L−1, non-monotonic dose-response suppression of H2O2 on M. aeruginosa were observed, where maximal cell death and minimal microcystin production both occurred at a moderate dose of 10 mg L−1 H2O2. Maximal cell death was indeed achieved through AL PCD, as revealed by integrated biochemical, structural, physiological and transcriptional evidence; transcriptional profile suggested AL PCD was mediated by mazEF and lexA systems. Higher H2O2 doses directly led to necrosis in M. aeruginosa, while lower doses only caused recoverable stress. The integrated data showed the choice between the two modes of cell death is determined by the intracellular energy state under stress. A model was proposed for suppressing M. aeruginosa with AL PCD or necrosis. H2O2 was demonstrated to simultaneously maximize the suppression of both growth and microcystin production through triggering AL PCD.

H

Expansion of penguin activity in maritime Antarctica, under ice thaw, increases the chances of penguin feces affecting soil microbiomes. The detail of such effects begins to be revealed. By comparing soil geochemistry and microbiome composition inside (one site) and outside (three sites) of the rookery, we found significant effects of penguin feces on both. First, penguin feces change soil geochemistry, causing increased moisture content (MC) of ornithogenic soils and nutrients C, N, P, and Si in the rookery compared to non-rookery sites, but not pH. Second, penguin feces directly affect microbiome composition in the rookery, not those outside. Specifically, we found 4,364 operational taxonomical units (OTUs) in 404 genera in six main phyla: Proteobacteria, Actinobacteria, Gemmatimonadetes, Acidobacteria, Chloroflexi, and Bacteroidetes. Although the diversity is similar among the four sites, the composition is different. For example, penguin rookery has a lower abundance of Acidobacteria, Chloroflexi, and Nitrospirae but a higher abundance of Bacteroidetes, Firmicutes, and Thermomicrobia. Strikingly, the family Clostridiaceae of Firmicutes of penguin-feces origin is most abundant in the rookery than non-rookery sites with two most abundant genera, Tissierella and Proteiniclasticum. Redundancy analysis showed all measured geochemical factors are significant in structuring microbiomes, with MC showing the highest correlation. We further extracted 21 subnetworks of microbes which contain 4,318 of the 4,364 OTUs using network analysis and are closely correlated with all geochemical factors except pH. Our finding f penguin feces, directly and indirectly, affects soil microbiome suggests an important role of penguins in soil geochemistry and microbiome structure of maritime Antarctica.

Metal exposure to terrestrial organism is influenced by the reactivity of the solid-phase metal pool. Aging is one of the important factors that control the reactivity of the solid-phase metal pool in soil. In this study, the selected 13 soils were collected from different locations of China, representing different soil types. The reactivity variation of spiked Cu and Zn with aging was assessed in these 13 soils, and their comparative toxicity potentials (CTPs) were also calculated. The median reactive fractions (freactive) of Cu and Zn with 95% confidence intervals were 1.6 × 10−2 (3.5 × 10−6 to 2.2 × 10−1) and 0.10 (9.1 × 10−4 to 0.44) kgreactive/kgtotal, and the median CTPs for Cu and Zn were 2.09 (8.1 × 10−4 to 2.2 × 104) and 0.85 (8.5 × 10−4 to 7.2 × 102) m3/kg day, respectively. The statistical analysis indicated that aging variability in the CTP of Cu and Zn was mainly associated with the variability in soil organic carbon and pH. These results stress the importance of dealing with aging in the calculation of CTPs for terrestrial ecotoxicity of metals.

Regulons, which serve as co-regulated gene groups contributing to the transcriptional regulation of microbial genomes, have the potential to aid in understanding of underlying regulatory mechanisms. In this study, we designed a novel computational pipeline, RECTA, for regulon prediction related to the gene regulatory network under certain conditions. To demonstrate the effectiveness of this tool, we implemented RECTA onLactococcus lactisMG1363 data to elucidate acid-response regulons.Lactococcus lactisis one of the most important Gram-positive lactic acid-producing bacteria, widely used in food industry and has been proved to have advantages in oral delivery of drug and vaccine. The pipeline carries out differential gene expression, gene co-expression analysis,cis-regulatory motif finding, and comparative genomics to predict and validate regulons related to acid stress response. A total of 51 regulonswere identified, 14 of which have computational-verified significance. Among these 14 regulons, five of them were computationally predicted to be connected with acid stress response with (i) known transcriptional factors in MEME suite database successfully mapped inLactococcus lactisMG1363; and (ii) differentially expressed genes between pH values of 6.5 (control) and 5.1 (treatment). Validated by 36 literature confirmed acid stress response related proteins and genes, 33 genes inLactococcus lactisMG1363 were found having orthologous genes using BLAST, associated to six regulons. An acid response related regulatory network was constructed, involving two trans-membrane proteins, eight regulons (llrA, llrC, hllA, ccpA, NHP6A,rcfB, regulons #8 and #39), nine functional modules, and 33 genes with orthologous genes known to be associated to acid stress. Our RECTA pipeline provides an effective way to construct a reliable gene regulatory network through regulon elucidation. The predicted response pathways could serve as promising candidates for better acid tolerance engineering inLactococcus lactis. RECTA has strong application power and can be effectively applied to other bacterial genomes where the elucidation of the transcriptional regulation network is needed.

In order to better understand the relationships among current Nostocales cyanobacterial blooms, eight genomes were sequenced from cultured isolates or from environmental metagenomes of recent planktonic Nostocales blooms. Phylogenomic analysis of publicly available sequences placed the new genomes among a group of 15 genomes from four continents in a distinct ADA clade (Anabaena/Dolichospermum/Aphanizomenon) within the Nostocales. This clade contains four species-level groups, two of which include members with both Anabaena-like and Aphanizomenon flos-aquae-like morphology. The genomes contain many repetitive genetic elements and a sizable pangenome, in which ABC-type transporters are highly represented. Alongside common core genes for photosynthesis, the differentiation of N2-fixing heterocysts, and the uptake and incorporation of the major nutrients P, N and S, we identified several gene pathways in the pangenome that may contribute to niche partitioning. Genes for problematic secondary metabolites—cyanotoxins and taste-and-odor compounds—were sporadically present, as were other polyketide synthase (PKS) and nonribosomal peptide synthetase (NRPS) gene clusters. By contrast, genes predicted to encode the ribosomally generated bacteriocin peptides were found in all genomes.

We present here an integrated analysis of structures and functions of genome-scale metabolic networks of 17 microorganisms. Our structural analyses of these networks revealed that the node degree of each network, represented as a (simplified) reaction network, follows a power-law distribution, and the clustering coefficient of each network has a positive correlation with the corresponding node degree. Together, these properties imply that each network has exactly one large and densely connected subnetwork or core. Further analyses revealed that each network consists of three functionally distinct subnetworks: (i) a core, consisting of a large number of directed reaction cycles of enzymes for interconversions among intermediate metabolites; (ii) a catabolic module, with a largely layered structure consisting of mostly catabolic enzymes; (iii) an anabolic module with a similar structure consisting of virtually all anabolic genes; and (iv) the three subnetworks cover on average ∼56, ∼31 and ∼13% of a network’s nodes across the 17 networks, respectively. Functional analyses suggest: (1) cellular metabolic fluxes generally go from the catabolic module to the core for substantial interconversions, then the flux directions to anabolic module appear to be determined by input nutrient levels as well as a set of precursors needed for macromolecule syntheses; and (2) enzymes in each subnetwork have characteristic ranges of kinetic parameters, suggesting optimized metabolic and regulatory relationships among the three subnetworks.

Background Helicobacter pylori is one of the most common pathogenic bacteria that causes chronic gastritis, peptic ulcers, and gastric cancer. It is very difficult to treat H. pylori bacterial infections, in part due to its polymorphisms. The objective of this study was to identify critical contributors to the pathogenicity of H. pylori bacteria through bibliometric screening of pathogenic genes. Methods The pathogenic genes of H. pylori strain 26695 were collected from major publication databases using the bibliometric approach. Information about the pathways, operons, and functions of these genes was obtained from the KEGG and DOOR databases. Results We inferred that HP0067, HP0069, HP1109, HP1036, and HP1037 are key pathogenic genes in H. pylori pathogenicity. These genes provided new targets for the clinical diagnosis and prognosis judgment of H. pylori. Conclusions Finally, this study may serve as a model for other genomic level studies when more H. pylori genomes become available. These results lay a theoretical foundation for further studies on the detection of novel pathogenic genes and relevant clinical analyses.

Aquatic organisms often suffer episodic stress from cyanobacterial bloom–derived concomitants and sometimes interactive stressors, and they may recover when stressors terminate. To assess whether exposed Daphnia can quickly recover from combined toxicity of bloom-derived stressors, Daphnia similoides were exposed to mixtures of ammonia (0 mg L−1, 0.37 mg L−1, and 0.58 mg L−1) and dissolved microcystin-LR (0 µg L−1, 10 µg L−1, 30 µg L−1, and 100 µg L−1) in a full factorial design for 14 d and subsequently allowed to recover for 7 d. During the exposure, the mixtures of ammonia and microcystin-LR showed different effects on the selected variables. Ammonia delayed the time to maturation, but microcystin-LR was not negative to the development of the tested daphnids. Furthermore, microcystin-LR reduced the prolonged developmental time to first eggs and first clutch caused by high ammonia. The total reproduction of D. similoides was dramatically reduced by 64% to 79% by both toxicants and their combinations, but there were no interactive effects. After the recovery period, organisms under most treatments did not recover completely from the combined stress but showed positive signs of recovery, based on the size of the last clutch and the mean number of clutches during recovery; thus the affected D. similoides have the potential to quickly recover from the combined toxic stressors. Environ Toxicol Chem 2014;33:2497–2505. © 2014 SETAC

Cohesins and dockerins are two groups of structural modules critical to the assembly of cellulosomes, the protein complexes for biomass degradation in cellulolytic microorganisms. To understand their sequence diversity and evolution, we re-mined five well-studied cellulosome-producing genomes in the order of Clostridiales for both domain modules and performed a comparative study. We found many putatively new cohesins and dockerins (designated as NEW) besides those identified previously (PUB). We showed that a significant number of NEW domain-containing proteins have signatures to be cellulosome-related, such as having CAZyme (carbohydrate-active enzymes) domains or other cellulosome-related domains, differentially expressed in cellulose degradation, having similar GC content and codon adaptation index as PUB domains. Evolutionary analyses suggest that NEW domains are more divergent in sequence than PUB domains, and PUB domains evolve more rapidly than CAZyme domains. Phylogenetic and functional domain analyses revealed that duplications play a major role in the expansion of dockerins and cohesins. For example, orthologous proteins of closely related strains have different numbers of cohesins, suggesting duplications occurred in a genome-specific manner after the strains diverged. High abundance of cohesin- and dockerin-containing proteins in Ruminococcus flavefaciens FD-1 and Acetivibrio cellulolyticus CD2, relative to Clostridium thermocellum, may be a result of gene duplication and horizontal gene transfer under relaxed purifying selection in environments with high species diversity. Overall, this study suggests that dockerins and cohesins evolve with a high rate of domain birth and death in cellulolytic microorganisms.

Understanding ethanol-induced stresses and responses in biofuel-producing bacteria at systems level has significant implications in engineering more efficient biofuel producers. We present a computational study of transcriptomic and genomic data of both ethanol-stressed and ethanol-adapted E. coli cells with computationally predicated ethanol-binding proteins and experimentally identified ethanol tolerance genes. Our analysis suggests: (1) ethanol damages cell wall and membrane integrity, causing increased stresses, particularly reactive oxygen species, which damages DNA and reduces the O2 level; (2) decreased cross-membrane proton gradient from membrane damage, coupled with hypoxia, leads to reduced ATP production by aerobic respiration, driving cells to rely more on fatty acid oxidation, anaerobic respiration and fermentation for ATP production; (3) the reduced ATP generation results in substantially decreased synthesis of macromolecules; (4) ethanol can directly bind 213 proteins including transcription factors, altering their functions; (5) all these changes together induce multiple stress responses, reduced biosynthesis, cell viability and growth; and (6) ethanol-adapted E. coli cells restore the majority of these reduced activities through selection of specific genomic mutations and alteration of stress responses, ultimately restoring normal ATP production, macromolecule biosynthesis, and growth. These new insights into the energy and mass balance will inform design of more ethanol-tolerant strains.

The degradation of cyanobacterial blooms often causes hypoxia and elevated concentrations of ammonia, which can aggravate the adverse effects of blooms on aquatic organisms. However, it is not clear how one stressor would work in the presence of other coexistent stressors. We studied the toxic effects of elevated ammonia under hypoxia using a common yet important cladoceran species Daphnia similis isolated from heavily eutrophicated Lake Taihu. A 3 × 2 factorial experimental design was conducted with animals exposed to three un-ionized ammonia levels under two dissolved oxygen levels. Experiments lasted for 14 days and we recorded the life-history traits such as survival, molt, maturation, and fecundity. Results showed that hypoxia significantly decreased survival time and the number of molts of D. similis, whereas ammonia had no effect on them. Elevated ammonia significantly delayed development to maturity in tested animals and decreased their body sizes at maturity. Both ammonia and hypoxia were significantly detrimental to the number of broods, the number of offspring per female, and the number of total offspring per female, and significantly synergistic interactions were detected. Our data clearly demonstrate that elevated ammonia and hypoxia derived from cyanobacterial blooms synergistically affect the cladoceran D. similis.

Although intraspecific competition plays a seminal role in organismal evolution, little is known about the fitness effects of mutations at different population densities. We identified a point mutation in the cyclic AMP receptor protein (CRP) gene in Escherichia coli that confers significantly higher fitness than the wildtype at low founding population density, but significantly lower fitness at high founding density. Because CRP is a transcription factor that regulates the expression of nearly 500 genes, we compared global gene expression profiles of the mutant and wildtype strains. This mutation (S63F) does not affect expression of crp itself, but it does significantly affect expression of 170 and 157 genes at high and low founding density, respectively. Interestingly, acid resistance genes, some of which are known to exhibit density-dependent effects in E. coli, were consistently differentially expressed at high but not low density. As such, these genes may play a key role in reducing the crp mutant’s fitness at high density, although other differentially expressed genes almost certainly also contribute to the fluctuating fitness differences we observed. Whatever the causes, we suspect that many mutations may exhibit density-dependent fitness effects in natural populations, so the fate of new mutations may frequently depend on the effective population size when they originate.

To investigate the changes in the morphology and polysaccharide content of Microcystis aeruginosa (Kütz.) Kütz. during flagellate grazing, cultures of M. aeruginosa were exposed to grazing Ochromonas sp. for a period of 9 d under controlled laboratory conditions. M. aeruginosa responded actively to flagellate grazing and formed colonies, most of which were made up of several or dozens of cells, suggesting that flagellate grazing may be one of the biotic factors responsible for colony formation in M. aeruginosa. When colonies were formed, the cell surface ultrastructure changed, and the polysaccharide layer on the surface of the cell wall became thicker. This change indicated that synthesis and secretion of extracellular polysaccharide (EPS) of M. aeruginosa cells increased under flagellate grazing pressure. The contents of soluble extracellular polysaccharide (sEPS), bound extracellular polysaccharide (bEPS), and total polysaccharide (TPS) in colonial cells of M. aeruginosa increased significantly compared with those in single cells. This finding suggested that the increased amount of EPS on the cell surface may play a role in keeping M. aeruginosa cells together to form colonies.

Insertion sequences (ISs) are transposable genetic elements in bacterial genomes. IS elements are common among bacteria but are generally rare within free-living species, probably because of the negative fitness effects they have on their hosts. Conversely, ISs frequently proliferate in intracellular symbionts and pathogens that recently transitioned from a free-living lifestyle. IS elements can profoundly influence the genomic evolution of their bacterial hosts, although it is unknown why they often expand in intracellular bacteria. We designed a laboratory evolution experiment with Escherichia coli K-12 to test the hypotheses that IS elements often expand in intracellular bacteria because of relaxed natural selection due to (1) their generally small effective population sizes (N (e)) and thus enhanced genetic drift, and (2) their nutrient rich environment, which makes many biosynthetic genes unnecessary and thus selectively neutral territory for IS insertion. We propagated 12 populations under four experimental conditions: large N (e) versus small N (e), and nutrient rich medium versus minimal medium. We found that relaxed selection over 4,000 generations was not sufficient to permit IS element expansion in any experimental population, thus leading us to hypothesize that IS expansion in intracellular symbionts may often be spurred by enhanced transposition rates, possibly due to environmental stress, coupled with relaxed natural selection.

Variation in colony size of Microcystis aeruginosa was investigated in Lake Taihu during recruitment and bloom formation from March to June. Single cells remained at the same level throughout the study period, making up between 30 and 40% of total units. Small colonies of 20 cells were not observed until mid-April. Much larger colonies composed of >200 cells were only observed occasionally in May but were frequent in June when a surface bloom formed in the lake, suggesting that colonies consisting of hundreds or thousands of cells are necessary to form blooms. Although the number of large colonies was small, the cells of these large colonies accounted for over 90% of the total population. The mean number of cells per colony increased significantly from May and reached over 120 in June, which coincided with bloom formation.

In order to monitor the changes of Microcystis along with temporal and spatial variations, seasonal variation of Microcystis in Lake Taihu was investigated by 16S-23S rRNA internal transcribed spacer denaturing gradient gel electrophoresis (16S-23S rRNA-ITS DGGE) and microscopic evaluation. Samples were collected quarterly at four sites (River Mouth, Meiliang Bay, Cross Area, and Lake Center) from August 2006 to April 2007. Results showed that Microcystis dominated total phytoplankton abundance at the four sites in all seasons except winter. The average annual abundance of Microcystis was relatively high at River Mouth and Meiliang Bay, reaching 81.22 x 10(6) and 61.32 x 10(6) cells/L, respectively. For temporal variations, Shannon-Wiener diversity index (H') according to DGGE profile revealed the richness of Microcystis in summer (H' = 1.375 +/- 0.034) and winter (H' = 1.650 +/- 0.032) was lower than that in spring (H' = 2.078 +/- 0.031) and autumn (H' = 2.365 +/- 0.032) (P0.05). While for spatial variations, the richness of Microcystis at River Mouth (H' = 2.015 +/- 0.074) was higher than at other sites during four seasons (P0.01). Very few differences of Microcystis diversity in the same season were observed among the other three sites (P0.05). Canonical correspondence analysis (CCA) was performed to elucidate the relationships between Microcystis operational taxonomic units (OTUs) composition and the environmental factors. Results of CCA revealed that temperature was strongly positively correlated with the first axis (r = 0.963), while TSS was negative correlated with the second axis (r = -0.716). Phylogenetic tree based on the sequencing results of target bands on DGGE gel indicated that samples collected in summer and winter constituted two separated clusters.

To investigate the changes in the morphology and polysaccharide content of Microcystis aeruginosa (Kutz.) Kutz. during flagellate grazing, cultures of M. aeruginosa were exposed to grazing Ochromonas sp. for a period of 9 d under controlled laboratory conditions. M. aeruginosa responded actively to flagellate grazing and formed colonies, most of which were made up of several or dozens of cells, suggesting that flagellate grazing may be one of the biotic factors responsible for colony formation in M. aeruginosa. When colonies were formed, the cell surface ultrastructure changed, and the polysaccharide layer on the surface of the cell wall became thicker. This change indicated that synthesis and secretion of extracellular polysaccharide (EPS) of M. aeruginosa cells increased under flagellate grazing pressure. The contents of soluble extracellular polysaccharide (sEPS), bound extracellular polysaccharide (bEPS), and total polysaccharide (TPS) in colonial cells of M. aeruginosa increased significantly compared with those in single cells. This finding suggested that the increased amount of EPS on the cell surface may play a role in keeping M. aeruginosa cells together to form colonies.

Variations of bacterioplankton community composition were monitored during Microcystis spp. blooms in Lake Taihu using denaturing gradient gel electrophoresis (DGGE) of amplified DNA fragments from April through November in 2005. Two sampling sites were selected—one in Meiliang Bay and the other in the center of the western region of the lake. The average abundance of Microcystis spp. was higher in Meiliang Bay than in the lake center, while the bacterioplankton community diversity of Meiliang Bay was significantly lower than that of the lake center (P < 0.05). Comparison of DGGE profiles indicated that in Meiliang Bay bacterioplankton communities decreased in band richness and species diversity as Microcystis spp. abundance increased. In the lake center, DGGE band number and Shannon index reached their peaks when Microcystis spp. blooms declined. The Shannon diversity index for the bacterioplankton community was negatively correlated with the Microcystis spp. abundance (r = −0.53, P = 0.10). Cha...