Microbiome Composition and Function Drives Wound-Healing Impairment in the Female Genital Tract

The mechanism(s) by which bacterial communities impact susceptibility to infectious diseases, such as HIV, and maintain female genital tract (FGT) health are poorly understood. Evaluation of FGT bacteria has predominantly been limited to studies of species abundance, but not bacterial function. We therefore sought to examine the relationship of bacterial community composition and function with mucosal epithelial barrier health in the context of bacterial vaginosis (BV) using metaproteomic, metagenomic, and in vitro approaches. We found highly diverse bacterial communities dominated by Gardnerella vaginalis associated with host epithelial barrier disruption and enhanced immune activation, and low diversity communities dominated by Lactobacillus species that associated with lower Nugent scores, reduced pH, and expression of host mucosal proteins important for maintaining epithelial integrity. Importantly, proteomic signatures of disrupted epithelial integrity associated with G. vaginalis-dominated communities in the absence of clinical BV diagnosis. Because traditional clinical assessments did not capture this, it likely represents a larger underrepresented phenomenon in populations with high prevalence of G. vaginalis. We finally demonstrated that soluble products derived from G. vaginalis inhibited wound healing, while those derived from L. iners did not, providing insight into functional mechanisms by which FGT bacterial communities affect epithelial barrier integrity

Metabolic Disturbances Associated with Systemic Lupus Erythematosus

The metabolic disturbances that underlie systemic lupus erythematosus are currently unknown. A metabolomic study was executed, comparing the sera of 20 SLE patients against that of healthy controls, using LC/MS and GC/MS platforms. Validation of key differences was performed using an independent cohort of 38 SLE patients and orthogonal assays. SLE sera showed evidence of profoundly dampened glycolysis, Krebs cycle, fatty acid β oxidation and amino acid metabolism, alluding to reduced energy biogenesis from all sources. Whereas long-chain fatty acids, including the n3 and n6 essential fatty acids, were significantly reduced, medium chain fatty acids and serum free fatty acids were elevated. The SLE metabolome exhibited profound lipid peroxidation, reflective of oxidative damage. Deficiencies were noted in the cellular anti-oxidant, glutathione, and all methyl group donors, including cysteine, methionine, and choline, as well as phosphocholines. The best discriminators of SLE included elevated lipid peroxidation products, MDA, gamma-glutamyl peptides, GGT, leukotriene B4 and 5-HETE. Importantly, similar elevations were not observed in another chronic inflammatory autoimmune disease, rheumatoid arthritis. To sum, comprehensive profiling of the SLE metabolome reveals evidence of heightened oxidative stress, inflammation, reduced energy generation, altered lipid profiles and a pro-thrombotic state. Resetting the SLE metabolome, either by targeting selected molecules or by supplementing the diet with essential fatty acids, vitamins and methyl group donors offers novel opportunities for disease modulation in this disabling systemic autoimmune ailment

Bacteria-Induced Dscam Isoforms of the Crustacean, Pacifastacus leniusculus

The Down syndrome cell adhesion molecule, also known as Dscam, is a member of the immunoglobulin super family. Dscam plays an essential function in neuronal wiring and appears to be involved in innate immune reactions in insects. The deduced amino acid sequence of Dscam in the crustacean Pacifastacus leniusculus (PlDscam), encodes 9(Ig)-4(FNIII)-(Ig)-2(FNIII)-TM and it has variable regions in the N-terminal half of Ig2 and Ig3 and the complete Ig7 and in the transmembrane domain. The cytoplasmic tail can generate multiple isoforms. PlDscam can generate more than 22,000 different unique isoforms. Bacteria and LPS injection enhanced the expression of PlDscam, but no response in expression occurred after a white spot syndrome virus (WSSV) infection or injection with peptidoglycans. Furthermore, PlDscam silencing did not have any effect on the replication of the WSSV. Bacterial specific isoforms of PlDscam were shown to have a specific binding property to each tested bacteria, E. coli or S. aureus. The bacteria specific isoforms of PlDscam were shown to be associated with bacterial clearance and phagocytosis in crayfish

Clinicopathologic and gene expression parameters predict liver cancer prognosis

<p>Abstract</p> <p>Background</p> <p>The prognosis of hepatocellular carcinoma (HCC) varies following surgical resection and the large variation remains largely unexplained. Studies have revealed the ability of clinicopathologic parameters and gene expression to predict HCC prognosis. However, there has been little systematic effort to compare the performance of these two types of predictors or combine them in a comprehensive model.</p> <p>Methods</p> <p>Tumor and adjacent non-tumor liver tissues were collected from 272 ethnic Chinese HCC patients who received curative surgery. We combined clinicopathologic parameters and gene expression data (from both tissue types) in predicting HCC prognosis. Cross-validation and independent studies were employed to assess prediction.</p> <p>Results</p> <p>HCC prognosis was significantly associated with six clinicopathologic parameters, which can partition the patients into good- and poor-prognosis groups. Within each group, gene expression data further divide patients into distinct prognostic subgroups. Our predictive genes significantly overlap with previously published gene sets predictive of prognosis. Moreover, the predictive genes were enriched for genes that underwent normal-to-tumor gene network transformation. Previously documented liver eSNPs underlying the HCC predictive gene signatures were enriched for SNPs that associated with HCC prognosis, providing support that these genes are involved in key processes of tumorigenesis.</p> <p>Conclusion</p> <p>When applied individually, clinicopathologic parameters and gene expression offered similar predictive power for HCC prognosis. In contrast, a combination of the two types of data dramatically improved the power to predict HCC prognosis. Our results also provided a framework for understanding the impact of gene expression on the processes of tumorigenesis and clinical outcome.</p

Sequence Defined Disulfide-Linked Shuttle for Strongly Enhanced Intracellular Protein Delivery

Intracellular protein transduction technology is opening the door for a promising alternative to gene therapy. Techniques have to address all critical steps, like efficient cell uptake, endolysosomal escape, low toxicity, while maintaining full functional activity of the delivered protein. Here, we present the use of a chemically precise, structure defined three-arm cationic oligomer carrier molecule for protein delivery. This carrier of exact and low molecular weight combines good cellular uptake with efficient endosomal escape and low toxicity. The protein cargo is covalently attached by a bioreversible disulfide linkage. Murine 3T3 fibroblasts could be transduced very efficiently with cargo nlsEGFP, which was tagged with a nuclear localization signal. We could show subcellular delivery of the nlsEGFP to the nucleus, confirming cytosolic delivery and expected subsequent subcellular trafficking. Transfection efficiency was concentration-dependent in a directly linear mode and 20-fold higher in comparison with HIV-TAT-nlsEGFP containing a functional TAT transduction domain. Furthermore, β-galactosidase as a model enzyme cargo, modified with the carrier oligomer, was transduced into neuroblastoma cells in enzymatically active form

Vaginal bacteria modify HIV tenofovir microbicide efficacy in African women.

CAPRISA, 2017.Abstract available in pdf

Identification of germline alterations of the mad homology 2 domain of SMAD3 and SMAD4 from the Ontario site of the breast cancer family registry (CFR)

Abstract Introduction A common feature of neoplastic cells is that mutations in SMADs can contribute to the loss of sensitivity to the anti-tumor effects of transforming growth factor-β (TGF-β). However, germline mutation analysis of SMAD3 and SMAD4, the principle substrates of the TGF-β signaling pathway, has not yet been conducted in breast cancer. Thus, it is currently unknown whether germline SMAD3 and SMAD4 mutations are involved in breast cancer predisposition. Methods We performed mutation analysis of the highly conserved mad-homology 2 (MH2) domains for both genes in genomic DNA from 408 non-BRCA1/BRCA2 breast cancer cases and 710 population controls recruited by the Ontario site of the breast cancer family registry (CFR) using denaturing high-performance liquid chromatography (DHPLC) and direct DNA sequencing. The results were interpreted in several ways. First, we adapted nucleotide diversity analysis to quantitatively assess whether the frequency of alterations differ between the two genes. Next, in silico tools were used to predict variants' effect on domain function and mRNA splicing. Finally, 37 cases or controls harboring alterations were tested for aberrant splicing using reverse-transcription polymerase chain reaction (PCR) and real-time PCR statistical comparison of germline expressions by non-parametric Mann-Whitney test of independent samples. Results We identified 27 variants including 2 novel SMAD4 coding variants c.1350G > A (p.Gln450Gln), and c.1701A > G (p.Ile525Val). There were no inactivating mutations even though c.1350G > A was predicted to affect exonic splicing enhancers. However, several additional findings were of note: 1) nucleotide diversity estimate for SMAD3 but not SMAD4 indicated that coding variants of the MH2 domain were more infrequent than expected; 2) in breast cancer cases SMAD3 was significantly over-expressed relative to controls (P A was associated with elevated germline expression (> 5-fold); 3) separate analysis using tissue expression data showed statistically significant over-expression of SMAD3 and SMAD4 in breast carcinomas. Conclusions This study shows that inactivating germline alterations in SMAD3 and SMAD4 are rare, suggesting a limited role in driving tumorigenesis. Nevertheless, aberrant germline expressions of SMAD3 and SMAD4 may be more common in breast cancer than previously suspected and offer novel insight into their roles in predisposition and/or progression of breast cancer

Hippocampal pyramidal cells: the reemergence of cortical lamination

The increasing resolution of tract-tracing studies has led to the definition of segments along the transverse axis of the hippocampal pyramidal cell layer, which may represent functionally defined elements. This review will summarize evidence for a morphological and functional differentiation of pyramidal cells along the radial (deep to superficial) axis of the cell layer. In many species, deep and superficial sublayers can be identified histologically throughout large parts of the septotemporal extent of the hippocampus. Neurons in these sublayers are generated during different periods of development. During development, deep and superficial cells express genes (Sox5, SatB2) that also specify the phenotypes of superficial and deep cells in the neocortex. Deep and superficial cells differ neurochemically (e.g. calbindin and zinc) and in their adult gene expression patterns. These markers also distinguish sublayers in the septal hippocampus, where they are not readily apparent histologically in rat or mouse. Deep and superficial pyramidal cells differ in septal, striatal, and neocortical efferent connections. Distributions of deep and superficial pyramidal cell dendrites and studies in reeler or sparsely GFP-expressing mice indicate that this also applies to afferent pathways. Histological, neurochemical, and connective differences between deep and superficial neurons may correlate with (patho-) physiological phenomena specific to pyramidal cells at different radial locations. We feel that an appreciation of radial subdivisions in the pyramidal cell layer reminiscent of lamination in other cortical areas may be critical in the interpretation of studies of hippocampal anatomy and function

Cross-ancestry genome-wide association analysis of corneal thickness strengthens link between complex and Mendelian eye diseases

Central corneal thickness (CCT) is a highly heritable trait associated with complex eye diseases such as keratoconus and glaucoma. We perform a genome-wide association meta-analysis of CCT and identify 19 novel regions. In addition to adding support for known connective tissue-related pathways, pathway analyses uncover previously unreported gene sets. Remarkably, >20% of the CCT-loci are near or within Mendelian disorder genes. These included FBN1, ADAMTS2 and TGFB2 which associate with connective tissue disorders (Marfan, Ehlers-Danlos and Loeys-Dietz syndromes), and the LUM-DCN-KERA gene complex involved in myopia, corneal dystrophies and cornea plana. Using index CCT-increasing variants, we find a significant inverse correlation in effect sizes between CCT and keratoconus (r =-0.62, P = 5.30 × 10-5) but not between CCT and primary open-angle glaucoma (r =-0.17, P = 0.2). Our findings provide evidence for shared genetic influences between CCT and keratoconus, and implicate candidate genes acting in collagen and extracellular matrix regulation

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License