Biology subjects

Ding, Y.

Publications and source records attributed to Ding, Y..

At least 19 recordsLinked to original sources

bioRxiv2018

Single-cell microRNA/mRNA co-sequencing reveals non-genetic heterogeneity and novel regulatory mechanisms

Co-measurement of multiple omic profiles from the same single cells opens up the opportunity to decode molecular regulation that underlie intercellular heterogeneity in development and disease. Here, we present co-sequencing of microRNAs and mRNAs in the same single cells using a half-cell genomics approach. This method demonstrates good robustness (~95% success rate) and reproducibility (R2=0.93 for both miRNAs and mRNAs), and yields paired half-cell miRNA and mRNA profiles that could be independently validated. Linking the level of miRNAs to the expression of predicted target mRNAs across 19 single cells that are phenotypically identical, we observe that the predicted targets are significantly anti-correlated with the variation of abundantly expressed miRNAs, suggesting that miRNA expression variability alone may lead to non-genetic cell-to-cell heterogeneity. Genome-scale analysis of paired miRNA-mRNA co-profiles further allows us to derive and validate new regulatory relationships of cellular pathways controlling miRNA expression and variability.

systems biology↗

bioRxiv2018

Adopting Literature-based Discovery on Rehabilitation Therapy Repositioning for Stroke

Stroke is a common disabling disease severely affecting the daily life of the patients. There is evidence that rehabilitation therapy can improve the movement function. However, there are no clear guidelines that identify specific, effective rehabilitation therapy schemes, and the development of new rehabilitation techniques has been fairly slow. One informatics translational approach, called ABC model in Literature-based Discovery, was used to mine an existing rehabilitation candidate which is most likely to be repositioned for stroke. As in the classic ABC model originated from Don Swanson, we built the internal links of stroke (A), assessment scales (B), rehabilitation therapies (C) in PubMed relating to upper limb function measurements for stroke patients. In the first step, with E-utility we retrieved both stroke related assessment scales and rehabilitation therapies records, and complied two datasets called Stroke_Scales and Stroke_Therapies, respectively. In the next step, we crawled all rehabilitation therapies co-occurred with the Stroke_Theapies, named as All_Therapies. Therapies that were already included in Stroke_Therapies were deleted from All_Therapies, so that the remaining therapies were the potential rehabilitation therapies, which could be repositioned for stroke after subsequent filtration by manual check. We identified the top ranked repositioning rehabilitation therapy following by subsequent clinical validation. Hand-arm bimanual intensive training (HABIT) ranked the first in our repositioning rehabilitation therapies list, with the most interaction links with Stroke_Scales. HABIT showed a significant improvement in clinical scores on assessment scales of Fugl-Meyer Assessment and Action Research Arm Test in the clinical validation on upper limb function for acute stroke patients. Based on the ABC model and clinical validation of the results, we put forward that HABIT as a promising rehabilitation therapy for stroke, which shows that the ABC model is an effective text mining approach for rehabilitation therapy repositioning. The results seem to be promoted in clinical knowledge discovery.\n\nAuthor SummaryIn the present study, we proposed a text mining approach to mining terms related to disease, rehabilitation therapy, and assessment scale from literature, with a subsequent ABC inference analysis to identify relationships of these terms across publications. The clinical validation demonstrated that our approach can be used to identify potential repositioning rehabilitation therapy strategies for stroke. Specifically, we identified a promising rehabilitation method called HABIT previously used in pediatric congenital hemiplegia. A subsequent clinical trial confirmed this as a highly promising rehabilitation therapy for stroke.

bioinformatics↗

bioRxiv2018

Three-Dimensional Histology of Whole Zebrafish by Sub-Micron Synchrotron X-ray Micro-Tomography

Histological studies providing cellular insights into tissue architecture have been central to biological discovery and remain clinically invaluable today. Extending histology to three dimensions would be transformational for research and diagnostics. However, three-dimensional histology is impractical using current techniques. We have customized sample preparation, synchrotron X-ray tomographic parameters, and three-dimensional image analysis to allow for complete histological phenotyping using whole larval and juvenile zebrafish. The resulting digital zebrafish can be virtually sectioned and visualized in any plane. Whole-animal reconstructions at subcellular resolution also enable computational characterization of the zebrafish nervous system by region-specific detection of cell nuclei and quantitative assessment of individual phenotypic variation. Three-dimensional histological phenotyping has potential use in genetic and chemical screens, and in clinical and toxicological tissue diagnostics.\n\nOne Sentence SummarySynchrotron X-ray micro-tomography can be used to rapidly create 3-dimensional images of fixed and stained specimens without sectioning, enabling computational histological phenotyping at cellular resolution.

pathology↗

bioRxiv2018

BAMM-SC: A Bayesian mixture model for clustering droplet-based single cell transcriptomic data from population studies

The recently developed droplet-based single cell transcriptome sequencing (scRNA-seq) technology makes it feasible to perform a population-scale scRNA-seq study, in which the transcriptome is measured for tens of thousands of single cells from multiple individuals. Despite the advances of many clustering methods, there are few tailored methods for population-scale scRNA-seq studies. Here, we have developed a BAyesiany Mixture Model for Single Cell sequencing (BAMM-SC) method to cluster scRNA-seq data from multiple individuals simultaneously. Specifically, BAMM-SC takes raw data as input and can account for data heterogeneity and batch effect among multiple individuals in a unified Bayesian hierarchical model framework. Results from extensive simulations and application of BAMM-SC to in-house scRNA-seq datasets using blood, lung and skin cells from humans or mice demonstrated that BAMM-SC outperformed existing clustering methods with improved clustering accuracy and reduced impact from batch effects. BAMM-SC has been implemented in a user-friendly R package with a detailed tutorial available on www.pitt.edu/~Cwec47/singlecell.html.

bioinformatics↗

bioRxiv2018

An integrative systems biology and experimental approach identifies convergence of epithelial plasticity, metabolism, and autophagy to promote chemoresistance

The evolution of therapeutic resistance is a major cause of death for patients with solid tumors. The development of therapy resistance is shaped by the ecological dynamics within the tumor microenvironment and the selective pressure induced by the host immune system. These ecological and selective forces often lead to evolutionary convergence on one or more pathways or hallmarks that drive progression. These hallmarks are, in turn, intimately linked to each other through gene expression networks. Thus, a deeper understanding of the evolutionary convergences that occur at the gene expression level could reveal vulnerabilities that could be targeted to treat therapy-resistant cancer. To this end, we used a combination of phylogenetic clustering, systems biology analyses, and wet-bench molecular experimentation to identify convergences in gene expression data onto common signaling pathways. We applied these methods to derive new insights about the networks at play during TGF-{beta}-mediated epithelial-mesenchymal transition in a lung cancer model system. Phylogenetics analyses of gene expression data from TGF-{beta} treated cells revealed evolutionary convergence of cells toward amine-metabolic pathways and autophagy during TGF-{beta} treatment. Using high-throughput drug screens, we found that knockdown of the autophagy regulatory, ATG16L1, re-sensitized lung cancer cells to cancer therapies following TGF-{beta}-induced resistance, implicating autophagy as a TGF-{beta}-mediated chemoresistance mechanism. Analysis of publicly-available clinical data sets validated the adverse prognostic importance of ATG16L expression in multiple cancer types including kidney, lung, and colon cancer patients. These analyses reveal the usefulness of combining evolutionary and systems biology methods with experimental validation to illuminate new therapeutic vulnerabilities.

cancer biology↗

bioRxiv2018

Population dynamics and transcriptomic responses of Pseudomonas aeruginosa in a complex laboratory microbial community

Pseudomonas aeruginosa is one of the dominant species when it co-exists with many other bacterial species in diverse environments. To understand its physiology and interactions with co-existing bacterial species in different conditions, we established physiologically reproducible eighteen-species communities, and found that P. aeruginosa became the dominant species in mixed-species biofilm community but not in the planktonic community. P. aeruginosa H1 type VI secretion system was highly induced in the mixed-species biofilm community compare to its mono-species biofilm, which was further demonstrated to play a key role for P. aeruginosa to gain fitness over other bacterial species. In addition, the type IV pili and Psl exopolysaccharide were shown to be required for P. aeruginosa to compete with other bacterial species in the biofilm community. Our study showed that the physiology of P. aeruginosa is strongly affected by interspecies interactions, and both biofilm determinants and H1 type VI secretion system contribute to P. aeruginosa fitness over other species in complex biofilm communities.\n\nImportancePseudomonas aeruginosa usually coexists with different bacterial species in natural environment. However, systematic comparative characterization of P. aeruginosa in complex microbial communities with its mono-species communities is lacking. We constructed mixed-species planktonic and biofilm communities consisting P. aeruginosa and seventeen other bacterial species to study the physiology and interaction of P. aeruginosa in complex multiple-species community. A single molecule detection platform, NanoString nCounter(R) 16S rRNA array, was used to shown that P. aeruginosa can become the dominant species in the biofilm communities while not in the planktonic communities. Comparative transcriptomic analysis and fluorescence-based quantification further revealed that P. aeruginosa H1 type VI secretion system and biofilm determinants are both required for its fitness in mixed-species biofilm communities.

microbiology↗

bioRxiv2018

Base pair editing of goat embryos: nonsense codon introgression into FGF5 to improve cashmere yield

The ability to alter single bases without DNA double strand breaks provides a potential solution for multiplex editing of livestock genomes for quantitative traits. Here, we report using a single base editing system, Base Editor 3 (BE3), to induce nonsense codons (C-to-T transitions) at four target sites in caprine FGF5. All five progenies produced from microinjected single-cell embryos had alleles with a targeted nonsense mutation and yielded expected phenotypes. The effectiveness of BE3 to make single base changes varied considerably based on sgRNA design. Also, the rate of mosaicism differed between animals, target sites, and tissue type. PCR amplicon and whole genome resequencing analyses for off-target changes caused by BE3 were low at a genome-wide scale. This study provides first evidence of base editing in livestock, thus presenting a potentially better method to introgress complex human disease alleles into large animal models and provide genetic improvement of complex health and production traits in a single generation.

genetics↗

bioRxiv2018

PANDA: A comprehensive and flexible tool for proteomics data quantitative analysis

SummaryAs the experiment techniques and strategies in quantitative proteomics are improving rapidly, the corresponding algorithms and tools for protein quantification with high accuracy and precision are continuously required to be proposed. Here, we present a comprehensive and flexible tool named PANDA for proteomics data quantification. PANDA, which supports both label-free and labeled quantifications, is compatible with existing peptide identification tools and pipelines with considerable flexibility. Compared with MaxQuant on two complex da-tasets, PANDA was proved to be more accurate and precise with less computation time. Additionally, PANDA is an easy-to-use desktop ap-plication tool with user-friendly interfaces.\n\nAvailabilityPANDA is freely available for download at https://sourceforge.net/projects/panda-tools/.\n\nContact1987ccpacer@163.com and zhuyunping@gmail.com

bioinformatics↗

bioRxiv2018

Ethylene signaling regulates natural variation in the abundance of antifungal acetylated diferuloylsucroses and Fusarium graminearum resistance in maize seedling roots

O_LIThe production and regulation of defensive specialized metabolites plays a central role in pathogen resistance in maize (Zea mays) and other plants. Therefore, identification of genes involved in plant specialized metabolism can contribute to improved disease resistance.\nC_LIO_LIWe used comparative metabolomics to identify previously unknown antifungal metabolites in maize seedling roots, and investigated the genetic and physiological mechanisms underlying their natural variation using quantitative trait locus (QTL) mapping and comparative transcriptomics approaches.\nC_LIO_LITwo maize metabolites, smilaside A (3,6-diferuloyl-3',6'-diacetylsucrose) and smiglaside C (3,6-diferuloyl-2',3',6'-triacetylsucrose), that may contribute to maize resistance against Fusarium graminearum and other fungal pathogens were identified. Elevated expression of an ethylene receptor gene, ETHYLENE INSENSITIVE 2 (ZmEIN2), co-segregated with decreased smilaside A/smiglaside C ratio. Pharmacological and genetic manipulation of ethylene availability and sensitivity in vivo indicated that, whereas ethylene was required for the production of both metabolites, the smilaside A/smiglaside C ratio was negatively regulated by ethylene sensitivity. This ratio, rather than the absolute abundance of these two metabolites, was important for maize seedling root defense against F. graminearum.\nC_LIO_LIEthylene signaling regulates the relative abundance of the two F. graminearum-resistance-related metabolites and affects resistance against F. graminearum in maize seedling roots.\nC_LI

plant biology↗

bioRxiv2018

Sub-voxel light-sheet microscopy for high-resolution, high-throughput volumetric imaging of large biomedical specimens

A key challenge when imaging whole biomedical specimens is how to quickly obtain massive cellular information over a large field of view (FOV). Here, we report a sub-voxel light-sheet microscopy (SLSM) method enabling high-throughput volumetric imaging of mesoscale specimens at cellular-resolution. A non-axial, continuous scanning strategy is used to rapidly acquire a stack of large-FOV images with three-dimensional (3-D) nanoscale shifts encoded. Then by adopting a sub-voxel-resolving procedure, the SLSM method models these low-resolution, cross-correlated images in the spatial domain and iteratively recovers a 3-D image with improved resolution throughout the sample. This technique can surpass the optical limit of a conventional light-sheet microscope by more than three times, with high acquisition speeds of gigavoxels per minute. As demonstrated by quick reconstruction (minutes to hours) of various samples, e.g., 3-D cultured cells, an intact mouse heart, mouse brain, and live zebrafish embryo, the SLSM method presents a high-throughput way to circumvent the tradeoff between intoto mapping of large-scale tissue (>100 mm3) and isotropic imaging of single-cell (~1-m resolution). It also eliminates the need of complicated mechanical stitching or precisely modulated illumination, using a simple light-sheet setup and fast graphics-processing-unit (GPU)-based computation to achieve high-throughput, high-resolution 3-D microscopy, which could be tailored for a wide range of biomedical applications in pathology, histology, neuroscience, etc.

bioengineering↗

bioRxiv2018

Rapid Whole Genome Sequencing Decreases Morbidity and Healthcare Cost of Hospitalized Infants

BACKGROUNDGenetic disorders are a leading cause of morbidity and mortality in infants. Rapid Whole Genome Sequencing (rWGS) can diagnose genetic disorders in time to change acute medical or surgical management (clinical utility) and improve outcomes in acutely ill infants.\n\nMETHODSRetrospective cohort study of acutely ill inpatient infants in a regional childrens hospital from July 2016-March 2017. Forty-two families received rWGS for etiologic diagnosis of genetic disorders. Probands received standard genetic testing as clinically indicated. Primary end-points were rate of diagnosis, clinical utility, and healthcare utilization. The latter was modelled in six infants by comparing actual utilization with matched historical controls and/or counterfactual utilization had rWGS been performed at different time points.\n\nFINDINGSThe diagnostic sensitivity was 43% (eighteen of 42 infants) for rWGS and 10% (four of 42 infants) for standard of care (P=.0005). The rate of clinical utility for rWGS (31%, thirteen of 42 infants) was significantly greater than for standard of care (2%, one of 42; P=.0015). Eleven (26%) infants with diagnostic rWGS avoided morbidity, one had 43% reduction in likelihood of mortality, and one started palliative care. In six of the eleven infants, the changes in management reduced inpatient cost by $800, 000 to $2,000,000.\n\nDISCUSSIONThese findings replicate a prior study of the clinical utility of rWGS in acutely ill inpatient infants, and demonstrate improved outcomes and net healthcare savings. rWGS merits consideration as a first tier test in this setting.

clinical trials↗

bioRxiv2017

Neural Changes Underlying Rapid Fly Song Evolution

The neural basis for behavioural evolution is poorly understood. Functional comparisons of homologous neurons may reveal how neural circuitry contributes to behavioural evolution, but homologous neurons cannot be identified and manipulated in most taxa. Here, we compare the function of homologous courtship song neurons by exporting neurogenetic reagents that label identified neurons in Drosophila melanogaster to D. yakuba. We found a conserved role for a cluster of brain neurons that establish a persistent courtship state. In contrast, a descending neuron with conserved electrophysiological properties drives different song types in each species. Our results suggest that song evolved, in part, due to changes in the neural circuitry downstream of this descending neuron. This experimental approach can be generalized to other neural circuits and therefore provides an experimental framework for studying how the nervous system has evolved to generate behavioural diversity.

evolutionary biology↗

bioRxiv2017

Human iPSC-derived RPE and retinal organoids reveal impaired alternative splicing of genes involved in pre-mRNA splicing in PRPF31 autosomal dominant retinitis pigmentosa

Mutations in pre-mRNA processing factors (PRPFs) cause 40% of autosomal dominant retinitis pigmentosa (RP), but it is unclear why mutations in ubiquitously expressed PRPFs cause retinal disease. To understand the molecular basis of this phenotype, we have generated RP type 11 (PRPF31-mutated) patient-specific retinal organoids and retinal pigment epithelium (RPE) from induced pluripotent stem cells (iPSC). Impaired alternative splicing of genes encoding pre-mRNA splicing proteins occurred in patient-specific retinal cells and Prpf31+/- mouse retinae, but not fibroblasts and iPSCs, providing mechanistic insights into retinal-specific phenotypes of PRPFs. RPE was the most affected, characterised by loss of apical-basal polarity, reduced trans-epithelial resistance, phagocytic capacity, microvilli, and cilia length and incidence. Disrupted cilia morphology was observed in patient-derived-photoreceptors that displayed progressive features associated with degeneration and cell stress. In situ gene-editing of a pathogenic mutation rescued key structural and functional phenotypes in RPE and photoreceptors, providing proof-of-concept for future therapeutic strategies.\n\neTOCPRPF31 is a ubiquitously expressed pre-mRNA processing factor that when mutated causes autosomal dominant RP. Using a patient-specific iPSC approach, Buskin and Zhu et al. show that retinal-specific defects result from altered splicing of genes involved in the splicing process itself, leading to impaired splicing, loss of RPE polarity and diminished phagocytic ability as well as reduced cilia incidence and length in both photoreceptors and RPE.\n\nHighlightsO_LISuccessful generation of iPSC-derived RPE and photoreceptors from four RP type 11 patients\nC_LIO_LIRPE cells express the mutant PRPF31 protein and show the lowest expression of wildtype protein\nC_LIO_LIPRPF31 mutations result in altered splicing of genes involved in pre-mRNA splicing in RPE and retinal organoids\nC_LIO_LIPrpf31 haploinsufficiency results in altered splicing of genes involved in pre-mRNA splicing in mouse retina\nC_LIO_LIRPE cells display loss of polarity, reduced barrier function and phagocytosis\nC_LIO_LIPhotoreceptors display shorter and fewer cilia and degenerative features\nC_LIO_LIRPE cells display most abnormalities suggesting they might be the primary site of pathogenesis\nC_LIO_LIIn situ gene editing corrects the mutation and rescues key phenotypes\nC_LI

genetics↗

bioRxiv2017

An interlaboratory study of complex variant detection

Next-generation sequencing (NGS) is widely used and cost-effective. Depending on the specific methods, NGS can have limitations detecting certain technically challenging variant types even though they are both prevalent in patients and medically important. These types are underrepresented in validation studies, hindering the uniform assessment of test methodologies by laboratory directors and clinicians. Specimens containing such variants can be difficult to obtain; thus, we evaluated a novel solution to this problem in which a diverse set of technically challenging variants was synthesized and introduced into a known genomic background. This specimen was sequenced by 7 laboratories using 10 different NGS workflows. The specimen was compatible with all 10 workflows and presented biochemical and bioinformatic challenges similar to those of patient specimens. Only 10 of 22 challenging variants were correctly identified by all 10 workflows, and only 3 workflows detected all 22. Many, but not all, of the sensitivity limitations were bioinformatic in nature. We conclude that Synthetic controls can provide an efficient and informative mechanism to augment studies with technically challenging variants that are difficult to obtain otherwise. Data from such specimens can facilitate inter-laboratory methodologic comparisons and can help establish standards that improve communication between clinicians and laboratories.

genetics↗

bioRxiv2017

Imaging-Genomics Study Of Head-Neck Squamous Cell Carcinoma: Associations Between Radiomic Phenotypes And Genomic Mechanisms Via Integration Of TCGA And TCIA

PurposeRecent data suggest that imaging radiomics features for a tumor could predict important genomic biomarkers. Understanding the relationship between radiomic and genomic features is important for basic cancer research and future patient care. For Head and Neck Squamous Cell Carcinoma (HNSCC), we perform a comprehensive study to discover the imaging-genomics associations and explore the potential of predicting tumor genomic alternations using radiomic features.\n\nMethodsOur retrospective study integrates whole-genome multi-omics data from The Cancer Genome Atlas (TCGA) with matched computed tomography imaging data from The Cancer Imaging Archive (TCIA) for the same set of 126 HNSCC patients. Linear regression analysis and gene set enrichment analysis are used to identify statistically significant associations between radiomic imaging features and genomic features. Random forest classifier is used to predict two key HNSCC molecular biomarkers, the status of human papilloma virus (HPV) and disruptive TP53 mutation, based on radiomic features.\n\nResultsWide-spread and statistically significant associations are discovered between genomic features (including miRNA expressions, protein expressions, somatic mutations, and transcriptional activities, copy number variations, and promoter region DNA methylation changes of pathways) and radiomic features characterizing the size, shape, and texture of tumor. Prediction of HPV and TP53 mutation status using radiomic features achieves an area under the receiver operating characteristics curve (AUC) of 0.71 and 0.641, respectively.\n\nConclusionOur analysis suggests that radiomic features are associated with genomic characteristics in HNSCC and provides justification for continued development of radiomics as biomarkers for relevant genomic alterations in HNSCC.

cancer biology↗

bioRxiv2017

An exact transformation of convolutional kernels applied directly to DNA/RNA sequences

MotivationConvolutional neural network (CNN) has been widely used in functional motifs identification for large-scale DNA/RNA sequences. Currently, however, the only way to interpret such a convolutional kernel is a heuristic construction of a position weight matrix (PWM) from fragments scored highly by that kernel.\n\nResultsInstead of using heuristics, we developed a novel, exact kernel-to-PWM transformation whose equivalency is theoretically proven: the log-likelihood of the resulting PWM generating any DNA/RNA sequence is exactly the sum of a constant and the convolution of the original kernel on the same sequence. Importantly, we further proved that the resulting PWMs performance on sequence classification/regression can be exactly the same as the original kernels under popular CNN frame-works. In simulation, the exact transformation rivals or outperforms the heuristic PWMs in terms of classifying sequences with sequence- or structure-motifs. The exact transformation also faithfully reproduces the output of CNN models on real-world cases, while the heuristic one fails, especially on the case with little prior knowledge on the form of underlying true motifs. Of note, the time complexity of the novel exact transformation is independent on the number of input sequences, enabling it to scale well for massive training sequences.\n\nAvailabilityPython scripts for the transformation from kernel to PWM, the inverted transformation from PWM to kernel, and a proof-of-concept for the maximum likelihood estimation of optimal PWM are available through https://github.com/gao-lab/kernel-to-PWM.\n\nContactgaog@mail.cbi.pku.edu.cn

bioinformatics↗

bioRxiv2017

The Acquisition of Resistance to Carbapenem and Macrolide-mediated Quorum Sensing Inhibition by Pseudomonas aeruginosa via a Novel Integrative and Conjugative Element ICETn43716385

Pseudomonas aeruginosa can cause persistant and life-threatening infections in immunocompromised patients. Carbapenems are the first-line agents to treat P. aeruginosa infections; therefore, the emergence of carbapenem-resistant P. aeruginosa strains has greatly challenged effective antibiotic therapy. In this study, we characterised the full-length genomes of two carbapenem resistant P. aeruginosa clinical isolates that produce the carbapebemase New Delhi metallo-{beta}-lactamase-1 (NDM-1). We found that the blaNDM-1 gene is encoded by a novel intergrative and conjugative element (ICE) ICETn43716385, which also carries the macrolide resistance gene msr(E) and the florfenicol resistance gene floR. The msr(E) gene has rarely been described in P. aeruginosa genomes. To investigate the functional roles of msr(E) in P. aeruginosa, we exogeneously expressed this gene in P. aeruginosa laboratory strains and found that the acquisition of msr(E) could abolish the azithromycin-mediated quorum sensing inhibition in vitro and the anti-Pseudomonas effect of azithromycin in vivo. In addition, the expression of msr(E) almost completely restored the azithromycin-affected P. aeruginosa transcriptome, as shown by our RNA sequencing analysis. We present the first evidence of blaNDM-1 to be carried by intergrative and conjugative elements, and the first evidence of co-transfer of carbapenem resistance and the resistance to macrolide-mediated quorum sensing inhibition into P. aeruginosa genomes.\n\nImportanceCarbapenem resistant P. aeruginosa has recently been listed as the top three most dangerous superbugs by World Health Organisation. The transmission of blaNDM-1 gene into P. aeruginosa can cause extreme resistance to carbapenems and fourth generation cephalosporins, which greatly compromises the effectiveness of these antibiotics against Pseudomonas infections. However, the lack of complete genome sequence of NDM-1-producing P. aeruginosa has limited our understanding of the transmisibility of blaNDM-1 in this organism. Here we showed the co-transfer of blaNDM-1 and msr(E) into P. aeruginosa genome by a novel integrative and conjugative element (ICE). The acquisition of these two genes confers P. aeruginosa with resistance to carbapenem and macrolide-mediated quorum sensing inhibition, both of which are important treatment stretagies for P. aeruginosa infections. Our findings highlight the potential of ICEs in transmitting carbapenem resistance, and that the anti-virulence treatment of P. aeruginosa infections by macrolides can be challenged by horizontal gene transfer.

genomics↗

bioRxiv2017

c-Maf-dependent regulatory T cells mediate immunological tolerance to intestinal microbiota

Both microbial and host genetic factors contribute to the pathogenesis of autoimmune disease1-4. Accumulating evidence suggests that microbial species that potentiate chronic inflammation, as in inflammatory bowel disease (IBD), often also colonize healthy individuals. These microbes, including the Helicobacter species, have the propensity to induce autoreactive T cells and are collectively referred to as pathobionts4-8. However, an understanding of how such T cells are constrained in healthy individuals is lacking. Here we report that host tolerance to a potentially pathogenic bacterium, Helicobacter hepaticus (H. hepaticus), is mediated by induction of ROR{gamma}t+Foxp3+ regulatory T cells (iTreg) that selectively restrain pro-inflammatory TH17 cells and whose function is dependent on the transcription factor c-Maf. Whereas H. hepaticus colonization of wild-type mice promoted differentiation of ROR{gamma}t-expressing microbe-specific iTreg in the large intestine, in disease-susceptible IL-10-deficient animals there was instead expansion of colitogenic TH17 cells. Inactivation of c-Maf in the Treg compartment likewise impaired differentiation of bacteria-specific iTreg, resulting in accumulation of H. hepaticus-specific inflammatory TH17 cells and spontaneous colitis. In contrast, ROR{gamma}t inactivation in Treg only had a minor effect on bacterial-specific Treg-TH17 balance, and did not result in inflammation. Our results suggest that pathobiont-dependent IBD is a consequence of microbiota-reactive T cells that have escaped this c-Maf-dependent mechanism of iTreg-TH17 homeostasis.

immunology↗