A transient receptor potential ion channel in Chlamydomonas shares key features with sensory transduction-associated TRP channels in mammals.

Sensory modalities are essential for navigating through an ever-changing environment. From insects to mammals, transient receptor potential (TRP) channels are known mediators for cellular sensing. Chlamydomonas reinhardtii is a motile single-celled freshwater green alga that is guided by photosensory, mechanosensory, and chemosensory cues. In this type of alga, sensory input is first detected by membrane receptors located in the cell body and then transduced to the beating cilia by membrane depolarization. Although TRP channels seem to be absent in plants, C. reinhardtii possesses genomic sequences encoding TRP proteins. Here, we describe the cloning and characterization of a C. reinhardtii version of a TRP channel sharing key features present in mammalian TRP channels associated with sensory transduction. In silico sequence-structure analysis unveiled the modular design of TRP channels, and electrophysiological experiments conducted on Human Embryonic Kidney-293T cells expressing the Cr-TRP1 clone showed that many of the core functional features of metazoan TRP channels are present in Cr-TRP1, suggesting that basic TRP channel gating characteristics evolved early in the history of eukaryotes.

The Structure-Function Linkage Database.

The Structure-Function Linkage Database (SFLD, http://sfld.rbvi.ucsf.edu/) is a manually curated classification resource describing structure-function relationships for functionally diverse enzyme superfamilies. Members of such superfamilies are diverse in their overall reactions yet share a common ancestor and some conserved active site features associated with conserved functional attributes such as a partial reaction. Thus, despite their different functions, members of these superfamilies 'look alike', making them easy to misannotate. To address this complexity and enable rational transfer of functional features to unknowns only for those members for which we have sufficient functional information, we subdivide superfamily members into subgroups using sequence information, and lastly into families, sets of enzymes known to catalyze the same reaction using the same mechanistic strategy. Browsing and searching options in the SFLD provide access to all of these levels. The SFLD offers manually curated as well as automatically classified superfamily sets, both accompanied by search and download options for all hierarchical levels. Additional information includes multiple sequence alignments, tab-separated files of functional and other attributes, and sequence similarity networks. The latter provide a new and intuitively powerful way to visualize functional trends mapped to the context of sequence similarity.

Prediction of function for the polyprenyl transferase subgroup in the isoprenoid synthase superfamily.

The number of available protein sequences has increased exponentially with the advent of high-throughput genomic sequencing, creating a significant challenge for functional annotation. Here, we describe a large-scale study on assigning function to unknown members of the trans-polyprenyl transferase (E-PTS) subgroup in the isoprenoid synthase superfamily, which provides substrates for the biosynthesis of the more than 55,000 isoprenoid metabolites. Although the mechanism for determining the product chain length for these enzymes is known, there is no simple relationship between function and primary sequence, so that assigning function is challenging. We addressed this challenge through large-scale bioinformatics analysis of >5,000 putative polyprenyl transferases; experimental characterization of the chain-length specificity of 79 diverse members of this group; determination of 27 structures of 19 of these enzymes, including seven cocrystallized with substrate analogs or products; and the development and successful application of a computational approach to predict function that leverages available structural data through homology modeling and docking of possible products into the active site. The crystallographic structures and computational structural models of the enzyme-ligand complexes elucidate the structural basis of specificity. As a result of this study, the percentage of E-PTS sequences similar to functionally annotated ones (BLAST e-value ≤ 1e(-70)) increased from 40.6 to 68.8%, and the percentage of sequences similar to available crystal structures increased from 28.9 to 47.4%. The high accuracy of our blind prediction of newly characterized enzymes indicates the potential to predict function to the complete polyprenyl transferase subgroup of the isoprenoid synthase superfamily computationally.

MACiE: exploring the diversity of biochemical reactions.

MACiE (which stands for Mechanism, Annotation and Classification in Enzymes) is a database of enzyme reaction mechanisms, and can be accessed from http://www.ebi.ac.uk/thornton-srv/databases/MACiE/. This article presents the release of Version 3 of MACiE, which not only extends the dataset to 335 entries, covering 182 of the EC sub-subclasses with a crystal structure available (~90%), but also incorporates greater chemical and structural detail. This version of MACiE represents a shift in emphasis for new entries, from non-homologous representatives covering EC reaction space to enzymes with mechanisms of interest to our users and collaborators with a view to exploring the chemical diversity of life. We present new tools for exploring the data in MACiE and comparing entries as well as new analyses of the data and new searches, many of which can now be accessed via dedicated Perl scripts.

Drug and gut microbe relationships: Moving beyond antibiotics.

Our understanding of drug-microbe relationships has evolved from viewing microbes as mere drug producers to a dynamic, modifiable system where they can serve as drugs or targets of precision pharmacology. This review highlights recent findings on the gut microbiome, particularly focusing on four aspects of research: (i) drugs for bugs, covering recent strategies for targeting gut pathogens; (ii) bugs as drugs, including probiotics; (iii) drugs from bugs, including postbiotics; and (iv) bugs and drugs, discussing additional types of drug-microbe interactions. This review provides a perspective on future translational research, including efficient companion diagnostics in pharmaceutical interventions.

Digital Therapeutics Care Utilizing Genetic and Gut Microbiome Signals for the Management of Functional Gastrointestinal Disorders: Results From a Preliminary Retrospective Study.

Diet and lifestyle-related illnesses including functional gastrointestinal disorders (FGIDs) and obesity are rapidly emerging health issues worldwide. Research has focused on addressing FGIDs via in-person cognitive-behavioral therapies, diet modulation and pharmaceutical intervention. Yet, there is paucity of research reporting on digital therapeutics care delivering weight loss and reduction of FGID symptom severity, and on modeling FGID status and symptom severity reduction including personalized genomic SNPs and gut microbiome signals. Our aim for this study was to assess how effective a digital therapeutics intervention personalized on genomic SNPs and gut microbiome signals was at reducing symptomatology of FGIDs on individuals that successfully lost body weight. We also aimed at modeling FGID status and FGID symptom severity reduction using demographics, genomic SNPs, and gut microbiome variables. This study sought to train a logistic regression model to differentiate the FGID status of subjects enrolled in a digital therapeutics care program using demographic, genetic, and baseline microbiome data. We also trained linear regression models to ascertain changes in FGID symptom severity of subjects at the time of achieving 5% or more of body weight loss compared to baseline. For this we utilized a cohort of 177 adults who reached 5% or more weight loss on the Digbi Health personalized digital care program, who were retrospectively surveyed about changes in symptom severity of their FGIDs and other comorbidities before and after the program. Gut microbiome taxa and demographics were the strongest predictors of FGID status. The digital therapeutics program implemented, reduced the summative severity of symptoms for 89.42% (93/104) of users who reported FGIDs. Reduction in summative FGID symptom severity and IBS symptom severity were best modeled by a mixture of genomic and microbiome predictors, whereas reduction in diarrhea and constipation symptom severity were best modeled by microbiome predictors only. This preliminary retrospective study generated diagnostic models for FGID status as well as therapeutic models for reduction of FGID symptom severity. Moreover, these therapeutic models generate testable hypotheses for associations of a number of biomarkers in the prognosis of FGIDs symptomatology.

Quantitative comparison of catalytic mechanisms and overall reactions in convergently evolved enzymes: implications for classification of enzyme function.

Functionally analogous enzymes are those that catalyze similar reactions on similar substrates but do not share common ancestry, providing a window on the different structural strategies nature has used to evolve required catalysts. Identification and use of this information to improve reaction classification and computational annotation of enzymes newly discovered in the genome projects would benefit from systematic determination of reaction similarities. Here, we quantified similarity in bond changes for overall reactions and catalytic mechanisms for 95 pairs of functionally analogous enzymes (non-homologous enzymes with identical first three numbers of their EC codes) from the MACiE database. Similarity of overall reactions was computed by comparing the sets of bond changes in the transformations from substrates to products. For similarity of mechanisms, sets of bond changes occurring in each mechanistic step were compared; these similarities were then used to guide global and local alignments of mechanistic steps. Using this metric, only 44% of pairs of functionally analogous enzymes in the dataset had significantly similar overall reactions. For these enzymes, convergence to the same mechanism occurred in 33% of cases, with most pairs having at least one identical mechanistic step. Using our metric, overall reaction similarity serves as an upper bound for mechanistic similarity in functional analogs. For example, the four carbon-oxygen lyases acting on phosphates (EC 4.2.3) show neither significant overall reaction similarity nor significant mechanistic similarity. By contrast, the three carboxylic-ester hydrolases (EC 3.1.1) catalyze overall reactions with identical bond changes and have converged to almost identical mechanisms. The large proportion of enzyme pairs that do not show significant overall reaction similarity (56%) suggests that at least for the functionally analogous enzymes studied here, more stringent criteria could be used to refine definitions of EC sub-subclasses for improved discrimination in their classification of enzyme reactions. The results also indicate that mechanistic convergence of reaction steps is widespread, suggesting that quantitative measurement of mechanistic similarity can inform approaches for functional annotation.

Local Network Properties of Soil and Rhizosphere Microbial Communities in Potato Plantations Treated with a Biological Product Are Important Predictors of Crop Yield.

Understanding the effectiveness and potential mechanism of action of agricultural biological products under different soil profiles and crops will allow more precise product recommendations based on local conditions and will ultimately result in increased crop yield. This study aimed to use bulk soil and rhizosphere microbial composition and structure to evaluate the potential effect of a Bacillus amyloliquefaciens inoculant (strain QST713) on potatoes and to explore its relationship with crop yield. We implemented next-generation sequencing (NGS) and bioinformatics approaches to assess the bacterial and fungal biodiversity in 185 soil samples, distributed over four different time points-from planting to harvest-from three different geographical locations in the United States. In addition to location and sampling time (which includes the difference between bulk soil and rhizosphere) as the main variables defining the microbiome composition, the microbial inoculant applied as a treatment also had a small but significant effect in fungal communities and a marginally significant effect in bacterial communities. However, treatment preserved the native communities without causing a detectable long-lasting effect on the alpha- and beta-diversity patterns after harvest. Using information about the application of the microbial inoculant and considering microbiome composition and structure data, we were able to train a Random Forest model to estimate if a bulk soil or rhizosphere sample came from a low- or high-yield block with relatively high accuracy (84.6%), concluding that the structure of fungal communities gives us more information as an estimator of potato yield than the structure of bacterial communities. IMPORTANCE Our results reinforce the notion that each cultivar on each location recruits a unique microbial community and that these communities are modulated by the vegetative growth stage of the plant. Moreover, inoculation of a Bacillus amyloliquefaciens strain QST713-based product on potatoes also changed the abundance of specific taxonomic groups and the structure of local networks in those locations where the product caused an increase in the yield. The data obtained, from in-field assays, allowed training a predictive model to estimate the yield of a certain block, identifying microbiome variables-especially those related to microbial community structure-even with a higher predictive power than the geographical location of the block (that is, the principal determinant of microbial beta-diversity). The methods described here can be replicated to fit new models in any other crop and to evaluate the effect of any agricultural input in the composition and structure of the soil microbiome.

Draft Genome Sequence of Blautia luti DSM 14534T, Isolated from Human Stool.

Here, we report the draft sequence of Blautia luti strain DSM 14534T, originally isolated from human feces. This draft contains 74 contigs, comprising 3,718,760 bp with a G+C content of 42.87%. The annotated draft contains 3,338 coding sequences (CDSs) and 110 RNA genes.

Gut microbiome composition and risk factors in a large cross-sectional IBS cohort.

Objective: Irritable bowel syndrome (IBS) is a common gastrointestinal disorder that is difficult to diagnose and treat due to its inherent heterogeneity and unclear aetiology. Although there is evidence suggesting the importance of the microbiome in IBS, this association remains poorly defined. In the current study, we aimed to characterise a large cross-sectional cohort of patients with self-reported IBS in terms of microbiome composition, demographics, and risk factors. Design: Individuals who had previously submitted a stool sample for 16S microbiome sequencing were sent a comprehensive survey regarding IBS diagnosis, demographics, health history, comorbidities, family history, and symptoms. Log ratio-transformed abundances of microbial taxa were compared between individuals reporting a diagnosis of IBS without any comorbidities and individuals reporting no health conditions. Univariable testing was followed by a multivariable logistic regression model controlling for relevant confounders. Results: Out of 6386 respondents, 1692 reported a diagnosis of IBS without comorbidities and 1124 reported no health conditions. We identified 3 phyla, 15 genera, and 19 species as significantly associated with IBS after adjustment for confounding factors. Demographic risk factors include a family history of gut disorders and reported use of antibiotics in the last year. Conclusion: The results of this study confirm important IBS risk factors in a large cohort and support a connection for microbiome compositional changes in IBS pathogenesis. The results also suggest clinical relevance in monitoring and investigating the microbiome in patients with IBS. Further, the exploratory models described here provide a foundation for future studies.

MACiE (Mechanism, Annotation and Classification in Enzymes): novel tools for searching catalytic mechanisms.

MACiE (Mechanism, Annotation and Classification in Enzymes) is a database of enzyme reaction mechanisms, and is publicly available as a web-based data resource. This paper presents the first release of a web-based search tool to explore enzyme reaction mechanisms in MACiE. We also present Version 2 of MACiE, which doubles the dataset available (from Version 1). MACiE can be accessed from http://www.ebi.ac.uk/thornton-srv/databases/MACiE/

Correction: 16S rRNA gene sequencing and healthy reference ranges for 28 clinically relevant microbial taxa from the human gut microbiome.

[This corrects the article DOI: 10.1371/journal.pone.0176555.].

The role of a sequencing-based clinical intestinal screening test in patients at high-risk for Clostridium difficile and other pathogens: a case report.

BACKGROUND: Hospitalization and antibiotic treatment can put patients at high risk for Clostridium difficile infection, where a disturbance of the gut microbiome allows for Clostridium difficile proliferation and associated symptoms, including mild, moderate, or severe diarrhea. Clostridium difficile infection is challenging to treat, often recurrent, and leads to almost 30,000 annual deaths in the USA alone. Here we present a case where SmartGut™, an at-home, self-administered sequencing-based clinical intestinal screening test, was used to identify the presence of Clostridium difficile in a patient with worsening diarrhea. Identification of this pathogen and subsequent treatment led to a significant improvement in symptoms. CASE PRESENTATION: The patient is a 29-year-old white woman with a history of severe irritable bowel syndrome with diarrhea, hemorrhoidectomy, and anal sphincterotomy complicated by a perianal fistula and perirectal abscesses that required extended courses of broad-spectrum antibiotics. In June 2016, she developed intermittent Clostridium difficile infections, which required continued antibiotic use. Months later she used an at-home, self-administered, intestinal microbial test, the first of which was negative for the presence of Clostridium difficile, but it detected the relative abundance of microbes associated with irritable bowel syndrome outside the healthy reference ranges. In the subsequent 2 months after the negative Clostridium difficile result, her gastrointestinal symptoms worsened dramatically. A second microbiome test resulted in a positive Clostridium difficile finding and continued abnormal microbial parameters, which led the treating physician to refer her to a gastroenterologist. Additional testing confirmed the presence of Clostridium difficile with a toxin-positive strain. She received treatment immediately and her gastrointestinal symptoms improved significantly over the next week. CONCLUSIONS: This case report suggests that more frequent DNA testing for Clostridium difficile infections may be indicated in patients that are at high-risk for Clostridium difficile infection, especially for patients with irritable bowel syndrome, and those who undergo gastrointestinal surgery and/or an extended antibiotic treatment. This report also shows that such testing could be effectively performed using at-home, self-administered sequencing-based clinical intestinal microbial screening tests. Further research is needed to investigate whether the observations reported here extrapolate to a larger cohort of patients.

A novel sequencing-based vaginal health assay combining self-sampling, HPV detection and genotyping, STI detection, and vaginal microbiome analysis.

The composition of the vaginal microbiome, including both the presence of pathogens involved in sexually transmitted infections (STI) as well as commensal microbiota, has been shown to have important associations for a woman's reproductive and general health. Currently, healthcare providers cannot offer comprehensive vaginal microbiome screening, but are limited to the detection of individual pathogens, such as high-risk human papillomavirus (hrHPV), the predominant cause of cervical cancer. There is no single test on the market that combines HPV, STI, and microbiome screening. Here, we describe a novel inclusive vaginal health assay that combines self-sampling with sequencing-based HPV detection and genotyping, vaginal microbiome analysis, and STI-associated pathogen detection. The assay includes genotyping and detection of 14 hrHPV types, 5 low-risk HPV types (lrHPV), as well as the relative abundance of 31 bacterial taxa of clinical importance, including Lactobacillus, Sneathia, Gardnerella, and 3 pathogens involved in STI, with high sensitivity, specificity, and reproducibility. For each of these taxa, reference ranges were determined in a group of 50 self-reported healthy women. The HPV sequencing portion of the test was evaluated against the digene High-Risk HPV HC2 DNA test. For hrHPV genotyping, agreement was 95.3% with a kappa of 0.804 (601 samples); after removal of samples in which the digene hrHPV probe showed cross-reactivity with lrHPV types, the sensitivity and specificity of the hrHPV genotyping assay were 94.5% and 96.6%, respectively, with a kappa of 0.841. For lrHPV genotyping, agreement was 93.9% with a kappa of 0.788 (148 samples), while sensitivity and specificity were 100% and 92.9%, respectively. This novel assay could be used to complement conventional cervical cancer screening, because its self-sampling format can expand access among women who would otherwise not participate, and because of its additional information about the composition of the vaginal microbiome and the presence of pathogens.

The chemistry of protein catalysis.

We report, for the first time, on the statistics of chemical mechanisms and amino acid residue functions that occur in enzyme reaction sequences using the MACiE database of 202 distinct enzyme reaction mechanisms as a knowledge base. MACiE currently holds representatives from each Enzyme Commission sub-subclass where there is an available crystal structure and sufficient evidence in the primary literature for a mechanism. Each catalytic step of every reaction sequence in MACiE is fully annotated, so that it includes the function of the catalytic residues involved in the reaction and the chemical mechanisms by which substrates are transformed into products. We show that the most catalytic amino acid residues are histidine, cysteine and aspartate, which are also the residues whose side-chains are more likely to serve as reactants, and that have the greatest versatility of function. We show that electrophilic reactions in enzymes are very rare, and the majority of enzyme reactions rely upon nucleophilic and general acid/base chemistry. However, although rare, radical (homolytic) reactions are much more common than electrophilic reactions. Thus, the majority of amino acid residues perform stabilisation roles (as spectators) or proton shuttling roles (as reactants). The analysis presented provides a better understanding of the mechanisms of enzyme catalysis and may act as an initial step in the validation and prediction of mechanism in an enzyme active site.

Using reaction mechanism to measure enzyme similarity.

The concept of reaction similarity has been well studied in terms of the overall transformation associated with a reaction, but not in terms of mechanism. We present the first method to give a quantitative measure of the similarity of reactions based upon their explicit mechanisms. Two approaches are presented to measure the similarity between individual steps of mechanisms: a fingerprint-based approach that incorporates relevant information on each mechanistic step; and an approach based only on bond formation, cleavage and changes in order. The overall similarity for two reaction mechanisms is then calculated using the Needleman-Wunsch alignment algorithm. An analysis of MACiE, a database of enzyme mechanisms, using our measure of similarity identifies some examples of convergent evolution of chemical mechanisms. In many cases, mechanism similarity is not reflected by similarity according to the EC system of enzyme classification. In particular, little mechanistic information is conveyed by the class level of the EC system.

Self-Sampling for Human Papillomavirus Testing: Increased Cervical Cancer Screening Participation and Incorporation in International Screening Programs.

In most industrialized countries, screening programs for cervical cancer have shifted from cytology (Pap smear or ThinPrep) alone on clinician-obtained samples to the addition of screening for human papillomavirus (HPV), its main causative agent. For HPV testing, self-sampling instead of clinician-sampling has proven to be equally accurate, in particular for assays that use nucleic acid amplification techniques. In addition, HPV testing of self-collected samples in combination with a follow-up Pap smear in case of a positive result is more effective in detecting precancerous lesions than a Pap smear alone. Self-sampling for HPV testing has already been adopted by some countries, while others have started trials to evaluate its incorporation into national cervical cancer screening programs. Self-sampling may result in more individuals willing to participate in cervical cancer screening, because it removes many of the barriers that prevent women, especially those in low socioeconomic and minority populations, from participating in regular screening programs. Several studies have shown that the majority of women who have been underscreened but who tested HPV-positive in a self-obtained sample will visit a clinic for follow-up diagnosis and management. In addition, a self-collected sample can also be used for vaginal microbiome analysis, which can provide additional information about HPV infection persistence as well as vaginal health in general.

16S rRNA gene sequencing and healthy reference ranges for 28 clinically relevant microbial taxa from the human gut microbiome.

Changes in the relative abundances of many intestinal microorganisms, both those that naturally occur in the human gut microbiome and those that are considered pathogens, have been associated with a range of diseases. To more accurately diagnose health conditions, medical practitioners could benefit from a molecular, culture-independent assay for the quantification of these microorganisms in the context of a healthy reference range. Here we present the targeted sequencing of the microbial 16S rRNA gene of clinically relevant gut microorganisms as a method to provide a gut screening test that could assist in the clinical diagnosis of certain health conditions. We evaluated the possibility of detecting 46 clinical prokaryotic targets in the human gut, 28 of which could be identified with high precision and sensitivity by a bioinformatics pipeline that includes sequence analysis and taxonomic annotation. These targets included 20 commensal, 3 beneficial (probiotic), and 5 pathogenic intestinal microbial taxa. Using stool microbiome samples from a cohort of 897 healthy individuals, we established a reference range defining clinically relevant relative levels for each of the 28 targets. Our assay quantifies 28 targets in the context of a healthy reference range and correctly reflected 38/38 verification samples of real and synthetic stool material containing known gut pathogens. Thus, we have established a method to determine microbiome composition with a focus on clinically relevant taxa, which has the potential to contribute to patient diagnosis, treatment, and monitoring. More broadly, our method can facilitate epidemiological studies of the microbiome as it relates to overall human health and disease.

Participation of the Salmonella OmpD porin in the infection of RAW264.7 macrophages and BALB/c mice.

Salmonella Typhimurium is the etiological agent of gastroenteritis in humans and enteric fever in mice. Inside these hosts, Salmonella must overcome hostile conditions to develop a successful infection, a process in which the levels of porins may be critical. Herein, the role of the Salmonella Typhimurium porin OmpD in the infection process was assessed for adherence, invasion and proliferation in RAW264.7 mouse macrophages and in BALB/c mice. In cultured macrophages, a ΔompD strain exhibited increased invasion and proliferation phenotypes as compared to its parental strain. In contrast, overexpression of ompD caused a reduction in bacterial proliferation but did not affect adherence or invasion. In the murine model, the ΔompD strain showed increased ability to survive and replicate in target organs of infection. The ompD transcript levels showed a down-regulation when Salmonella resided within cultured macrophages and when it colonized target organs in infected mice. Additionally, cultured macrophages infected with the ΔompD strain produced lower levels of reactive oxygen species, suggesting that down-regulation of ompD could favor replication of Salmonella inside macrophages and the subsequent systemic dissemination, by limiting the reactive oxygen species response of the host.

Toward mechanistic classification of enzyme functions.

Classification of enzyme function should be quantitative, computationally accessible, and informed by sequences and structures to enable use of genomic information for functional inference and other applications. Large-scale studies have established that divergently evolved enzymes share conserved elements of structure and common mechanistic steps and that convergently evolved enzymes often converge to similar mechanisms too, suggesting that reaction mechanisms could be used to develop finer-grained functional descriptions than provided by the Enzyme Commission (EC) system currently in use. Here we describe how evolution informs these structure-function mappings and review the databases that store mechanisms of enzyme reactions along with recent developments to measure ligand and mechanistic similarities. Together, these provide a foundation for new classifications of enzyme function.