Prospective functional classification of all possible missense variants in PPARG.

Clinical exome sequencing routinely identifies missense variants in disease-related genes, but functional characterization is rarely undertaken, leading to diagnostic uncertainty. For example, mutations in PPARG cause Mendelian lipodystrophy and increase risk of type 2 diabetes (T2D). Although approximately 1 in 500 people harbor missense variants in PPARG, most are of unknown consequence. To prospectively characterize PPARγ variants, we used highly parallel oligonucleotide synthesis to construct a library encoding all 9,595 possible single-amino acid substitutions. We developed a pooled functional assay in human macrophages, experimentally evaluated all protein variants, and used the experimental data to train a variant classifier by supervised machine learning. When applied to 55 new missense variants identified in population-based and clinical sequencing, the classifier annotated 6 variants as pathogenic; these were subsequently validated by single-variant assays. Saturation mutagenesis and prospective experimental characterization can support immediate diagnostic interpretation of newly discovered missense variants in disease-related genes.This work was supported by grants from the National Institute of Diabetes and Digestive and Kidney Diseases (1K08DK102877-01, to A.R.M.; 1R01DK097768-01, to D.A.), NIH/Harvard Catalyst (1KL2TR001100-01, to A.R.M.), the Broad Institute (SPARC award, to A.R.M. and T.M.), and the Wellcome Trust (095564, to K.C.; 107064, to D.B.S.).This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.370

An approach for collaborative development of a federated biomedical knowledge graph-based question-answering system: Question-of-the-Month challenges

Knowledge graphs have become a common approach for knowledge representation. Yet, the application of graph methodology is elusive due to the sheer number and complexity of knowledge sources. In addition, semantic incompatibilities hinder efforts to harmonize and integrate across these diverse sources. As part of The Biomedical Translator Consortium, we have developed a knowledge graph-based question-answering system designed to augment human reasoning and accelerate translational scientific discovery: the Translator system. We have applied the Translator system to answer biomedical questions in the context of a broad array of diseases and syndromes, including Fanconi anemia, primary ciliary dyskinesia, multiple sclerosis, and others. A variety of collaborative approaches have been used to research and develop the Translator system. One recent approach involved the establishment of a monthly "Question-of-the-Month (QotM) Challenge" series. Herein, we describe the structure of the QotM Challenge; the six challenges that have been conducted to date on drug-induced liver injury, cannabidiol toxicity, coronavirus infection, diabetes, psoriatic arthritis, and ATP1A3-related phenotypes; the scientific insights that have been gleaned during the challenges; and the technical issues that were identified over the course of the challenges and that can now be addressed to foster further development of the prototype Translator system. We close with a discussion on Large Language Models such as ChatGPT and highlight differences between those models and the Translator system

The Type 2 Diabetes Knowledge Portal: an Open access Genetic Resource Dedicated to Type 2 Diabetes and Related Traits

Associations between human genetic variation and clinical phenotypes have become a foundation of biomedical research. Most repositories of these data seek to be disease-agnostic and therefore lack disease-focused views. The Type 2 Diabetes Knowledge Portal (T2DKP) is a public resource of genetic datasets and genomic annotations dedicated to type 2 diabetes (T2D) and related traits. Here, we seek to make the T2DKP more accessible to prospective users and more useful to existing users. First, we evaluate the T2DKP\u27s comprehensiveness by comparing its datasets with those of other repositories. Second, we describe how researchers unfamiliar with human genetic data can begin using and correctly interpreting them via the T2DKP. Third, we describe how existing users can extend their current workflows to use the full suite of tools offered by the T2DKP. We finally discuss the lessons offered by the T2DKP toward the goal of democratizing access to complex disease genetic results

Progress toward a universal biomedical data translator.

Clinical, biomedical, and translational science has reached an inflection point in the breadth and diversity of available data and the potential impact of such data to improve human health and well-being. However, the data are often siloed, disorganized, and not broadly accessible due to discipline-specific differences in terminology and representation. To address these challenges, the Biomedical Data Translator Consortium has developed and tested a pilot knowledge graph-based Translator system capable of integrating existing biomedical data sets and translating those data into insights intended to augment human reasoning and accelerate translational science. Having demonstrated feasibility of the Translator system, the Translator program has since moved into development, and the Translator Consortium has made significant progress in the research, design, and implementation of an operational system. Herein, we describe the current system\u27s architecture, performance, and quality of results. We apply Translator to several real-world use cases developed in collaboration with subject-matter experts. Finally, we discuss the scientific and technical features of Translator and compare those features to other state-of-the-art, biomedical graph-based question-answering systems

Expression of a constitutively activated plasma membrane H+-ATPase in Nicotiana tabacum BY-2 cells results in cell expansion

Increased acidification of the external medium by an activated H (+) -ATPase results in cell expansion, in the absence of upstream activating signaling. The plasma membrane H(+)-ATPase couples ATP hydrolysis with proton transport outside the cell, and thus creates an electrochemical gradient, which energizes secondary transporters. According to the acid growth theory, this enzyme is also proposed to play a major role in cell expansion, by acidifying the external medium and so activating enzymes that are involved in cell wall-loosening. However, this theory is still debated. To challenge it, we made use of a plasma membrane H(+)-ATPase isoform from Nicotiana plumbaginifolia truncated from its C-terminal auto-inhibitory domain (ΔCPMA4), and thus constitutively activated. This protein was expressed in Nicotiana tabacum BY-2 suspension cells using a heat shock inducible promoter. The characterization of several independent transgenic lines showed that the expression of activated ΔCPMA4 resulted in a reduced external pH by 0.3-1.2 units, as well as in an increased H(+)-ATPase activity by 77-155 % (ATP hydrolysis), or 70-306 % (proton pumping) of isolated plasma membranes. In addition, ΔCPMA4-expressing cells were 17-57 % larger than the wild-type cells and displayed abnormal shapes. A proteomic comparison of plasma membranes isolated from ΔCPMA4-expressing and wild-type cells revealed the altered abundance of several proteins involved in cell wall synthesis, transport, and signal transduction. In conclusion, the data obtained in this work showed that H(+)-ATPase activation is sufficient to induce cell expansion and identified possible actors which intervene in this process

Bacillus subtilis M4 decreases plant susceptibility towards fungal pathogens by increasing host resistance associated with differential gene expression

Results presented in this paper describe the ability of Bacillus subtilis strain M4 to reduce disease incidence caused by Colletotrichum lagenarium and Pythium aphanidermatum on cucumber and tomato, respectively. Disease protection in both pathosystems was most probably due to induction of resistance in the host plant since experiments were designed in order to avoid any direct contact between the biocontrol agent and the pathogen. Pre-inoculation with strain M4 thus sensitised both plants to react more efficiently to subsequent pathogen infection. In cucumber, the use of endospores provided a disease control level similar to that obtained with vegetative cells. In contrast, a mixture of lipopeptides from the surfactin, iturin and fengycin families showed no resistance-inducing potential. Interestingly, treatment with strain M4 was also associated with significant changes in gene transcription in the host plant as revealed by cDNA-AFLP analyses. Several AFLP fragments corresponded to genes not expressed in control plants and specifically induced by the Bacillus treatment. In support to the macroscopic protective effect, this differential accumulation of mRNA also illustrates the plant reaction following perception of strain M4, and constitutes one of the very first examples of defence-associated modifications at the transcriptional level elicited by a non-pathogenic bacterium in a host plant