Biology subjects

Levine, A.

Publications and source records attributed to Levine, A..

5 recordsLinked to original sources

bioRxiv2018

Immune profiling of cord blood after prolonged rupture of membranes.

We hypothesised that foetal immune responses to an infectious challenge may be detected by genome-wide transcriptional profiling of cord blood. In order to test this hypothesis, we sought to identify transcriptomic changes in post-natal cord blood samples following prolonged pre-labour rupture of membranes (PROM) as a surrogate for increased risk of infection. By comparison to controls we found increased levels of blood transcripts in a subset of prolonged PROM cases, significantly enriched for innate immune system signalling pathways. These changes were idiosyncratic, suggesting qualitative and quantitative variation in foetal immune responses which may reflect differences in exposure and/or in host genetics. Our data support the view that PROM represents an infection risk to the foetus. In addition, we propose that cord blood transcriptional profiling offers exciting opportunities to identify immune correlates of clinical outcome following potential in utero exposures to infection. These may be used to elucidate the mechanisms of immunological protection and pathology in the foetus and identify biomarkers to stratify the risk of adverse outcomes.

immunology↗

bioRxiv2018

Treatment-Specific Composition of Gut Microbiota Is Associated with Disease Remission in a Pediatric Crohn’s Disease Cohort

BackgroundThe beneficial effects of antibiotics in Crohns disease (CD) depend in part on the gut microbiota but are inadequately understood. We investigated the impact of metronidazole (MET) and metronidazole plus azithromycin (MET+AZ) on the microbiota in pediatric CD, and the use of microbiota features as classifiers or predictors of disease remission.\n\nMethods16S rRNA-based microbiota profiling was performed on stool samples from 67 patients in a multinational, randomized, controlled, longitudinal, 12-week trial of MET vs. MET+AZ in children with mild to moderate CD. Profiles were analyzed together with disease activity, and then used to construct Random Forest models to classify remission or predict treatment response.\n\nResultsBoth MET and MET+AZ significantly decreased diversity of the microbiota and caused large treatment-specific shifts in microbiota structure at week 4. Disease remission was associated with a treatment-specific microbiota configuration. Random Forest models constructed from microbiota profiles pre- and during antibiotic treatment with metronidazole accurately classified disease remission in this treatment group (AUC of 0.879, 95% CI 0.683, 0.9877; sensitivity 0.7778; specificity 1.000, P < 0.001). A Random Forest model trained on preantibiotic microbiota profiles predicted disease remission at week 4 with modest accuracy (AUC of 0.8, P = 0.24).\n\nConclusionsMET and MET+AZ antibiotic regimens in pediatric CD lead to distinct gut microbiota structures at remission. It may be possible to classify and predict remission based in part on microbiota profiles, but larger cohorts will be needed to realize this goal.\n\nSummaryWe investigated the impact of metronidazole and metronidazole plus azithromycin on the gut microbiota in pediatric Crohns disease. Disease remission was associated with a treatment-specific microbiota configuration, and could be predicted based on pre-antibiotic microbiota profiles.

microbiology↗

bioRxiv2017

WorMachine: Machine Learning-Based Phenotypic Analysis Tool for Worms

While Caenorhabditis elegans nematodes are powerful model organisms, quantification of visible phenotypes is still often labor-intensive, biased, and error-prone. We developed \"WorMachine\", a three-step MATLAB-based image analysis software that allows automated identification of C. elegans worms, extraction of morphological features, and quantification of fluorescent signals. The program offers machine learning techniques which should aid in studying a large variety of research questions. We demonstrate the power of WorMachine using five separate assays: scoring binary and continuous sexual phenotypes, quantifying the effects of different RNAi treatments, and measuring intercellular protein aggregation. Thus, WorMachine is a \"quick and easy\", high-throughput, automated, and unbiased analysis tool for measuring phenotypes.

bioinformatics↗

bioRxiv2017

Simultaneous cell traction and growth measurements using light

Understanding cell mechanotransduction is important for discerning matrix structure-cell function relationships underlying health and disease. Despite the crucial role of mechanochemical signaling in phenomena such as cell migration, proliferation, and differentiation, measuring the cell-generated forces at the interface with the extracellular matrix during these biological processes remains challenging. An ideal method would provide continuous, non-destructive images of the force field applied by cells, over broad spatial and temporal scales, while simultaneously revealing the cell biological process under investigation. Toward this goal, we present the integration of a new real-time traction stress imaging modality, Hilbert phase dynamometry (HPD), with the technique of spatial light interference microscopy (SLIM) for label free monitoring of cell growth. HPD relies on extracting the displacement field in a deformable substrate, which is chemically patterned with a fluorescent grid. The displacements introduced by the cell are captured by the phase of the periodic signal associated with the grid, borrowing concepts from holography. The displacement field is uniquely converted into forces by solving an elasticity inverse problem. Because the measurement of displacement only uses the epi-fluorescence channel of an inverted microscope, we can simultaneously achieve measurements in transmission. We performed SLIM and extracted cell mass on the same field of view in addition to the measured displacement field. We used this technique to study mesenchymal stem cells and found that cells undergoing osteogenesis and adipogenesis exerted larger and more dynamic stresses than their precursor. Our results indicate that the MSCs develop the smallest forces and growth rates. We anticipate that simultaneous cell growth and traction measurements will improve our understanding of mechanotransduction, particularly during dynamic processes where the matrix properties provide context to guide cells towards a physiological or pathological outcome, e.g., tissue morphogenesis, or cancer metastasis.

cell biology↗

bioRxiv2016

Mouse T cell repertoires as statistical ensembles: overall characterization and age dependence

The ability of the adaptive immune system to respond to arbitrary pathogens stems from the broad diversity of immune cell surface receptors (TCRs). This diversity originates in a stochastic DNA editing process (VDJ recombination) that acts each time a new immune cell is created from a stem cell. By analyzing T cell sequence repertoires taken from the blood and thymus of mice of different ages, we quantify the significant changes in this process that occur in development from embryo to young adult. We find a rapid increase with age in the number of random insertions in the VDJ recombination process, leading to a dramatic increase in diversity. Since the blood accumulates thymic output over time, blood repertoires are mixtures of different statistical recombination processes and, by unraveling the mixture statistics, we can obtain a clear picture of the time evolution of the early immune system. Sequence repertoire analysis also allows us to detect the effect of selection on the output of the VDJ recombination process. The effects we find are nearly identical between thymus and blood, suggesting that they mainly reflect selection for proper folding of the TCR receptor protein.

immunology↗