iBench: A ground truth approach for advanced validation of mass spectrometry identification method

The discovery of many noncanonical peptides detectable with sensitive mass spectrometry inside, outside, and on cells shepherded the development of novel methods for their identification, often not supported by a systematic benchmarking with other methods. We here propose iBench, a bioinformatic tool that can construct ground truth proteomics datasets and cognate databases, thereby generating a training court wherein methods, search engines, and proteomics strategies can be tested, and their performances estimated by the same tool. iBench can be coupled to the main database search engines, allows the selection of customized features of mass spectrometry spectra and peptides, provides standard benchmarking outputs, and is open source. The proof-of-concept application to tryptic proteome digestions, immunopeptidomes, and synthetic peptide libraries dissected the impact that noncanonical peptides could have on the identification of canonical peptides by Mascot search with rescoring via Percolator (Mascot+Percolator)

inSPIRE: An open-source tool for increased mass spectrometry identification rates using Prosit spectral prediction

Rescoring of mass spectrometry (MS) search results using spectral predictors can strongly increase Peptide Spectrum Match (PSM) identification rates. This approach is particularly effective when aiming to search MS data against large databases, for example when dealing with non-specific cleavage in immunopeptidomics or inflation of the reference database for noncanonical peptide identification. Here, we present inSPIRE (in silico Spectral Predictor Informed REscoring), a flexible and performant open-source rescoring pipeline built on Prosit MS spectral prediction, which is compatible with common database search engines. inSPIRE allows large scale rescoring with data from multiple MS search files, increases sensitivity to minor differences in amino acid residue position, and can be applied to various MS sample types, including tryptic proteome digestions and immunopeptidomes. inSPIRE boosts PSM identification rates in immunopeptidomics, leading to better performance than the original Prosit rescoring pipeline, as confirmed by benchmarking of inSPIRE performance on ground truth datasets. The integration of various features in the inSPIRE backbone further boosts the PSM identification in immunopeptidomics, with a potential benefit for the identification of noncanonical peptides

Evaluation of microbial communities associated with the liquid and solid phases of the rumen of cattle offered a diet of perennial ryegrass or white clover

Rumen microbiota plays an important role in animal productivity, methane production and health. Several different locations have been used to obtain rumen samples (i.e., liquid-phase samples, solid-phase samples, buccal swabs) in previous studies. Here we assess differences in the rumen microbiota between solid- and liquid-phases of the rumen under differing dietary conditions (white clover vs. perennial ryegrass); there were 4 sample types: liquid-associated/grass (LG), solid-associated/grass (SG), liquid-associated/clover (LC), and solid-associated/clover (SC). Four Holstein-Friesian cows were strip grazed on pure stands of perennial ryegrass or white clover in a change-over design experiment with 3 periods (each lasting for 3 weeks). Solid- and liquid- phase microbes were obtained following total rumen evacuation on the penultimate day of each period. DNA was extracted and multiplexed libraries sequenced using 16S next generation sequencing (Illumina MiSeq). Demultiplexed sequences underwent quality control and taxonomic profiles were generated for each sample. Statistical analysis for the effects of diet and phase was conducted both overall [using non-metric multidimensional scaling (NMDS) and diversity indices] and for individual taxa. Separation of both diet and phase was observed NMDS, with significant effects of diet (P < 0.001) and phase (P < 0.001) being observed. Regardless of diet, Prevotella was most abundant in the liquid samples. When assessing differences between phases, the majority of statistically significant taxa (predominantly from Archaea and the order Clostridiales) were found at higher relative abundances in solid-phase samples. Diversity (Shannon Index) was lower in the liquid-phase samples, possibly because of the higher relative abundance of Prevotella. A presence vs. absence approach, followed by Chi-squared testing, was adopted. Differences between phases (LG vs. LC, LC vs. LG, SG vs. SC, and SC vs. SG) and differences between phases for the clover diet (LC vs. SC and SC vs. LC) were significant (P < 0.001); differences between phases for the grass diet were non-significant. Sampling technique has a profound impact on reported microbial communities, which must be taken into consideration, particularly as archaea may be underestimated in the liquid-phase.</p

Links between the rumen microbiota, methane emissions and feed efficiency of finishing steers offered dietary lipid and nitrate supplementation

peer-reviewedRuminant methane production is a significant energy loss to the animal and major contributor to global greenhouse gas emissions. However, it also seems necessary for effective rumen function, so studies of anti-methanogenic treatments must also consider implications for feed efficiency. Between-animal variation in feed efficiency represents an alternative approach to reducing overall methane emissions intensity. Here we assess the effects of dietary additives designed to reduce methane emissions on the rumen microbiota, and explore relationships with feed efficiency within dietary treatment groups. Seventy-nine finishing steers were offered one of four diets (a forage/concentrate mixture supplemented with nitrate (NIT), lipid (MDDG) or a combination (COMB) compared to the control (CTL)). Rumen fluid samples were collected at the end of a 56 d feed efficiency measurement period. DNA was extracted, multiplexed 16s rRNA libraries sequenced (Illumina MiSeq) and taxonomic profiles were generated. The effect of dietary treatments and feed efficiency (within treatment groups) was conducted both overall (using non-metric multidimensional scaling (NMDS) and diversity indexes) and for individual taxa. Diet affected overall microbial populations but no overall difference in beta-diversity was observed. The relative abundance of Methanobacteriales (Methanobrevibacter and Methanosphaera) increased in MDDG relative to CTL, whilst VadinCA11 (Methanomassiliicoccales) was decreased. Trimethylamine precursors from rapeseed meal (only present in CTL) probably explain the differences in relative abundance of Methanomassiliicoccales. There were no differences in Shannon indexes between nominal low or high feed efficiency groups (expressed as feed conversion ratio or residual feed intake) within treatment groups. Relationships between the relative abundance of individual taxa and feed efficiency measures were observed, but were not consistent across dietary treatments

Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: an inter-laboratory study.

Antimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial-susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a 'one-stop' test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants, and identify problem cases and factors that lead to discordant results. We produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams ('participants') were provided these sequence data without any other contextual information. Each participant used their choice of pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime. We found participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results, but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment, a different antibiotic would have been recommended for each isolate by at least one participant. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases, full recommendations on sequence data quality and standardization in the comparisons between genotype and resistance phenotypes will all play a fundamental role in the successful implementation of AST prediction using WGS in clinical microbiology laboratories

Global endometrial transcriptomic profiling: transient immune activation precedes tissue proliferation and repair in healthy beef cows

peer-reviewedBackground: All cows experience bacterial contamination and tissue injury in the uterus postpartum, instigating a local inflammatory immune response. However mechanisms that control inflammation and achieve a physiologically functioning endometrium, while avoiding disease in the postpartum cow are not succinctly defined. This study aimed to identify novel candidate genes indicative of inflammation resolution during involution in healthy beef cows. Previous histological analysis of the endometrium revealed elevated inflammation 15 days postpartum (DPP) which was significantly decreased by 30 DPP. The current study generated a genome-wide transcriptomic profile of endometrial biopsies from these cows at both time points using mRNA-Seq. The pathway analysis tool GoSeq identified KEGG pathways enriched by significantly differentially expressed genes at both time points. Novel candidate genes associated with inflammatory resolution were subsequently validated in additional postpartum animals using quantitative real-time PCR (qRT-PCR). Results: mRNA-Seq revealed 1,107 significantly differentially expressed genes, 73 of which were increased 15 DPP and 1,034 were increased 30 DPP. Early postpartum, enriched immune pathways (adjusted P < 0.1) included the T cell receptor signalling pathway, graft-versus-host disease and cytokine-cytokine receptor interaction pathways. However 30 DPP, where the majority of genes were differentially expressed, the enrichment (adjusted P < 0.1) of tissue repair and proliferative activity pathways was observed. Nineteen candidate genes selected from mRNA-Seq results, were independently assessed by qRT-PCR in additional postpartum cows (5 animals) at both time points. SAA1/2, GATA2, IGF1, SHC2, and SERPINA14 genes were significantly elevated 30 DPP and are functionally associated with tissue repair and the restoration of uterine homeostasis postpartum. Conclusions: The results of this study reveal an early activation of the immune response which undergoes a temporal functional change toward tissue proliferation and regeneration during endometrial involution in healthy postpartum cows. These molecular changes mirror the activation and resolution of endometrial inflammation during involution previously classified by the degree of neutrophil infiltration. SAA1/2, GATA2, IGF1, SHC2, and SERPINA14 genes may become potential markers for resolution of endometrial inflammation in the postpartum cow

Differentially Expressed Genes in Endometrium and Corpus Luteum of Holstein Cows Selected for High and Low Fertility Are Enriched for Sequence Variants Associated with Fertility

peer-reviewedDespite the importance of fertility in humans and livestock, there has been little success dissecting the genetic basis of fertility. Our hypothesis was that genes differentially expressed in the endometrium and corpus luteum on Day 13 of the estrous cycle between cows with either good or poor genetic merit for fertility would be enriched for genetic variants associated with fertility. We combined a unique genetic model of fertility (cattle that have been selected for high and low fertility and show substantial difference in fertility) with gene expression data from these cattle and genome-wide association study (GWAS) results in ∼20 000 cattle to identify quantitative trait loci (QTL) regions and sequence variants associated with genetic variation in fertility. Two hundred and forty-five QTL regions and 17 sequence variants associated primarily with prostaglandin F2alpha, steroidogenesis, mRNA processing, energy status, and immune-related processes were identified. Ninety-three of the QTL regions were validated by two independent GWAS, with signals for fertility detected primarily on chromosomes 18, 5, 7, 8, and 29. Plausible causative mutations were identified, including one missense variant significantly associated with fertility and predicted to affect the protein function of EIF4EBP3. The results of this study enhance our understanding of 1) the contribution of the endometrium and corpus luteum transcriptome to phenotypic fertility differences and 2) the genetic architecture of fertility in dairy cattle. Including these variants in predictions of genomic breeding values may improve the rate of genetic gain for this critical trait

Adverse pregnancy outcomes and long-term risk of maternal renal disease: a systematic review and meta-analysis protocol

Introduction: Adverse pregnancy outcomes, such as hypertensive disorders of pregnancy (HDP), gestational diabetes (GDM) and preterm birth have been linked to maternal cardiovascular disease in later life. Pre-eclampsia (PE) is associated with an increased risk of postpartum microalbuminuria, but there is no clear consensus on whether HDP increases the risk of maternal chronic kidney disease (CKD) and end-stage kidney disease (ESKD). Similarly, it is uncertain whether GDM, preterm birth and delivery of low birth-weight infants independently predict the risk of maternal renal disease in later life. The aims of this proposed systematic review and meta-analysis are to summarise the available evidence examining the association between adverse outcomes of pregnancy (HDP, GDM, preterm birth, delivery of low birth-weight infant) and later maternal renal disease and to synthesise the results of relevant studies. Methods and analysis: A systematic search of PubMed, EMBASE and Web of Science will be undertaken using a detailed prespecified search strategy. Two authors will independently review the titles and abstracts of all studies, perform data extraction and appraise the quality of included studies using a bias classification tool. Original case–control and cohort studies published in English will be considered for inclusion. Primary outcomes of interest will be CKD and ESKD; secondary outcomes will be hospitalisation for renal disease and deaths from renal disease. Meta-analyses will be performed to calculate the overall pooled estimates using the generic inverse variance method. The systematic review will follow the Meta-analyses Of Observational Studies in Epidemiology guidelines. Ethics and dissemination: This systematic review and meta-analysis will be based on published data, and thus there is no requirement for ethics approval. The results will be shared through publication in a peer reviewed journal and through presentations at academic conferences. PROSPERO registration number CRD4201811089