Biology subjects

Martin, N.

Publications and source records attributed to Martin, N..

6 recordsLinked to original sources

bioRxiv2018

Deciphering the enigmatic role of the amidotransferase LipL in Bacillus subtilis lipoic acid utilization

Lipoate is an essential cofactor for key enzymes of oxidative and one-carbon metabolism. It is covalently attached to E2 subunits of dehydrogenase (DH) complexes and the GcvH subunit of the glycine cleavage system. Bacillus subtilis possess two protein lipoylation pathways: biosynthesis and scavenging. The former requires octanoylation of GcvH, amidotransfer of the octanoate to E2s, and insertion of sulfur atoms. Lipoate scavenging is mediated by a lipoate ligase (LplJ), that catalizes a classical two-step ATP-dependent reaction. Although these pathways were thought to be redundant, a {Delta}lipL mutant, unable to transfer the octanoyl group from GcvH to the E2s during lipoate synthesis, showed growth defects in minimal media even when supplemented with this cofactor, despite the presence of a functional LplJ. In this study we demonstrated that LipL is essential to modify E2 subunits of branched chain ketoacid and pyruvate DH during lipoate scavenging. LipL must be functional and it is not forming a complex with LplJ, which suggests that these enzymes might be acting sequentially. We also show that the E2 subunit of oxoglutarate DH is a good donor for LipL amidotransfer reaction. The essential role of LipL during lipoate utilization relies on the strict substrate specificity of LplJ, determined by charge complementarity between the ligase and the lipoylable subunits. LplJ does not recognize E2 subunits without a negatively charged residue in key positions of the target protein, and thus LipL is required to transfer the lipoate to them. This model of lipoate scavenging seems widespread among Gram-positive bacteria.

microbiology↗

bioRxiv2018

Integrative analysis of transcriptomic and clinical data uncovers the tumor suppressive activity of MITF in prostate cancer.

The dysregulation of gene expression is an enabling hallmark of cancer. Computational analysis of transcriptomics data from human cancer specimens, complemented with exhaustive clinical annotation, provides an opportunity to identify core regulators of the tumorigenic process. Here we exploit well-annotated clinical datasets of prostate cancer for the discovery of transcriptional regulators relevant to prostate cancer. Following this rationale, we identify Microphthalmia-associated transcription factor (MITF) as a prostate tumor suppressor among a subset of transcription factors. Importantly, we further interrogate transcriptomics and clinical data to refine MITF perturbation-based empirical assays and unveil Crystallin Alpha B (CRYAB) as an unprecedented direct target of the transcription factor that is, at least in part, responsible for its tumor suppressive activity in prostate cancer. This evidence was supported by the enhanced prognostic potential of a signature based on the concomitant alteration of MITF and CRYAB in prostate cancer patients. In sum, our study provides proof-of-concept evidence of the potential of the bioinformatics screen of publicly available cancer patient databases as discovery platforms, and demonstrates that the MITF-CRYAB axis controls prostate cancer biology.

cancer biology↗

bioRxiv2018

A systems biology approach to explore the impact of maple tree dormancy release on sap variation and maple syrup quality

Maple sap is a complex nutrient matrix collected during Spring to produce maple syrup. The characteristics of sap change over the production period and its composition directly impacts syrup quality. This variability could in part be attributed to changes in tree metabolism following dormancy release, but little is known about these changes in deciduous trees. Therefore, understanding the variation in sap composition associated with dormancy release could help pinpoint the causes of some defects in maple syrup. In particular, a defect known as \"buddy\", is an increasing concern for the industry. This off-flavor appears around the time of bud burst, hence its name. To investigate sap variation related to bud burst and the buddy defect, we monitored sap variation with respect to a dormancy release index (Sbb) and syrup quality. First, we looked at variation in amino acid content during this period. We observed a shift in amino acid relative proportions associated with dormancy release and found that most of them increase rapidly near the point of bud burst, correlating with changes in syrup quality. Second, we identified biological processes that respond to variation in maple sap by performing a competition assay using the barcoded Saccharomyces cerevisiae prototroph deletion collection. This untargeted approach revealed that the organic sulfur content may be responsible for the development of the buddy off-flavor, and that dormancy release is necessary for the appearance of the defect, but other factors such as microbial activity may also be contributing.

plant biology↗

bioRxiv2018

Interim impact evaluation of the hepatitis C virus elimination program in Georgia

Background and AimsGeorgia has one of the highest hepatitis C virus (HCV) prevalence rates in the world, with >5% of the adult population (~150,000 people) chronically infected. In April 2015, the Georgian government, in collaboration with CDC and other partners, launched a national program to eliminate HCV through scaling up HCV treatment and prevention interventions, with the aim of achieving a 90% reduction in prevalence by 2020. We evaluate the interim impact of the HCV treatment program as of 31 October 2017, and assess the feasibility of achieving the elimination goal by 2020.\n\nMethodWe developed a dynamic HCV transmission model to capture the current and historical epidemic dynamics of HCV in Georgia, including the main drivers of transmission. Using the 2015 national sero-survey and prior surveys conducted among people who inject drugs (PWID) from 1997-2015, the model was calibrated to data on HCV prevalence by age, gender and PWID status, and the age distribution of PWID. We use the model to project the interim impact of treatment strategies currently being undertaken as part of the ongoing Georgia HCV elimination program, while accounting for treatment failure/loss to follow up, in order to determine whether they are on track to achieving their HCV elimination target by 2020, or whether strategies need to be modified to ensure success.\n\nResultsA treatment rate of 2,050 patients/month was required from the beginning of the national program to achieve a 90% reduction in prevalence by the end of 2020, with equal treatment rates of PWID and the general population. From May 2015 to October 2017, 40,420 patients were treated, an average of ~1,350 per month; although the treatment rate has recently declined from a peak of 4,500/month in September 2016 to 2100/month in November-December 2016, and 1000/month in August-October 2017, with a sustained virological response rate (SVR) of 98% per-protocol or 78% intent to treat. The model projects that the treatments undertaken up to October 2017 have reduced adult chronic prevalence by 26% (18-35%) to 3.7% (2.9-5.1%), reduced total incidence by 25% (15-35%), and prevented 1845 (751-3969) new infections and 93 (31-177) HCV-related deaths. If the treatment rate of 1000 patients initiated per month continues, prevalence will have halved by 2020, and reduce by 90% by 2026. In order to reach a 90% reduction by 2020, the treatment rate must increase 3.5-fold to 4000/month.\n\nConclusionThe Georgia HCV elimination program has accomplished an impressive scale up of treatment, which has already impacted on prevalence and incidence, and averted deaths due to HCV. However, extensive scale up is needed to achieve a 90% reduction in prevalence by 2020.

epidemiology↗

bioRxiv2017

Genome-wide association analysis links multiple psychiatric liability genes to oscillatory brain activity

Oscillations in neuronal activity are widely thought to play a crucial role in information processing and cortical communication 1-8. Brain oscillations have been widely investigated as biomarkers of psychiatric disorders and variation in normal human behavior 9, 10, including intelligence 11, 12, schizophrenia 13, 14, attentional deficits 15, 16, and substance use 17, 18. Beyond the biomarker, oscillatory activity may indeed cause variation in behavior, as it has been shown that disrupting oscillatory activity by blocking GABAergic fast-spiking interneurons in the frontal cortex of mice impairs behavioral flexibility8, consistent with ...

genetics↗

bioRxiv2017

Do Candidate Genes Affect the Brain’s White Matter Microstructure? Large-Scale Evaluation of 6,165 Diffusion MRI Scans

AbstractSusceptibility genes for psychiatric and neurological disorders - including APOE, BDNF, CLU,CNTNAP2, COMT, DISC1, DTNBP1, ErbB4, HFE, NRG1, NTKR3, and ZNF804A - have been reported to affect white matter (WM) microstructure in the healthy human brain, as assessed through diffusion tensor imaging (DTI). However, effects of single nucleotide polymorphisms (SNPs) in these genes explain only a small fraction of the overall variance and are challenging to detect reliably in single cohort studies. To date, few studies have evaluated the reproducibility of these results. As part of the ENIGMA-DTI consortium, we pooled regional fractional anisotropy (FA) measures for 6,165 subjects (CEU ancestry N=4,458) from 11 cohorts worldwide to evaluate effects of 15 candidate SNPs by examining their associations with WM microstructure. Additive association tests were conducted for each SNP. We used several meta-analytic and mega-analytic designs, and we evaluated regions of interest at multiple granularity levels. The ENIGMA-DTI protocol was able to detect single-cohort findings as originally reported. Even so, in this very large sample, no significant associations remained after multiple-testing correction for the 15 SNPs investigated. Suggestive associations (1.3x10-4 < p < 0.05, uncorrected) were found for BDNF, COMT, and ZNF804A in specific tracts. Meta-and mega-analyses revealed similar findings. Regardless of the approach, the previously reported candidate SNPs did not show significant associations with WM microstructure in this largest genetic study of DTI to date; the negative findings are likely not due to insufficient power. Genome-wide studies, involving large-scale meta-analyses, may help to discover SNPs robustly influencing WM microstructure.

neuroscience↗