Chemical cross-linking/mass spectrometry targeting acidic residues in proteins and protein complexes

The study of proteins and protein complexes using chemical cross-linking followed by the MS identification of the cross-linked peptides has found increasingly widespread use in recent years. Thus far, such analyses have used almost exclusively homobifunctional, amine-reactive cross-linking reagents. Here we report the development and application of an orthogonal cross-linking chemistry specific for carboxyl groups. Chemical cross-linking of acidic residues is achieved using homobifunctional dihydrazides as cross-linking reagents and a coupling chemistry at neutral pH that is compatible with the structural integrity of most protein complexes. In addition to cross-links formed through insertion of the dihydrazides with different spacer lengths, zero-length cross-link products are also obtained, thereby providing additional structural information. We demonstrate the application of the reaction and the MS identification of the resulting cross-linked peptides for the chaperonin TRiC/CCT and the 26S proteasome. The results indicate that the targeting of acidic residues for cross-linking provides distance restraints that are complementary and orthogonal to those obtained from lysine cross-linking, thereby expanding the yield of structural information that can be obtained from cross-linking studies and used in hybrid modeling approaches

Inhibition of the \u3cem\u3edapE\u3c/em\u3e-Encoded \u3cem\u3eN\u3c/em\u3e-Succinyl- ʟ, ʟ-diaminopimelic Acid Desuccinylase from \u3cem\u3eNeisseria meningitidis\u3c/em\u3e by ʟ-Captopril

Binding of the competitive inhibitor ʟ-captopril to the dapE-encoded N-succinyl-ʟ, ʟ-diaminopimelic acid desuccinylase from Neisseria meningitidis (NmDapE) was examined by kinetic, spectroscopic, and crystallographic methods. ʟ-Captopril, an angiotensin-converting enzyme (ACE) inhibitor, was previously shown to be a potent inhibitor of the DapE from Haemophilus influenzae (HiDapE) with an IC50 of 3.3 μM and a measured Ki of 1.8 μM and displayed a dose-responsive antibiotic activity toward Escherichia coli. ʟ-Captopril is also a competitive inhibitor of NmDapE with a Ki of 2.8 μM. To examine the nature of the interaction of ʟ-captopril with the dinuclear active site of DapE, we have obtained electron paramagnetic resonance (EPR) and magnetic circular dichroism (MCD) data for the enzymatically hyperactive Co(II)-substituted forms of both HiDapE and NmDapE. EPR and MCD data indicate that the two Co(II) ions in DapE are antiferromagnetically coupled, yielding an S = 0 ground state, and suggest a thiolate bridge between the two metal ions. Verification of a thiolate-bridged dinuclear complex was obtained by determining the three-dimensional X-ray crystal structure of NmDapE in complex with ʟ-captopril at 1.8 Å resolution. Combination of these data provides new insights into binding of ʟ-captopril to the active site of DapE enzymes as well as important inhibitor–active site residue interaction’s. Such information is critical for the design of new, potent inhibitors of DapE enzymes

Functional responses of methanogenic archaea to syntrophic growth.

Methanococcus maripaludis grown syntrophically with Desulfovibrio vulgaris was compared with M. maripaludis monocultures grown under hydrogen limitation using transcriptional, proteomic and metabolite analyses. These measurements indicate a decrease in transcript abundance for energy-consuming biosynthetic functions in syntrophically grown M. maripaludis, with an increase in transcript abundance for genes involved in the energy-generating central pathway for methanogenesis. Compared with growth in monoculture under hydrogen limitation, the response of paralogous genes, such as those coding for hydrogenases, often diverged, with transcripts of one variant increasing in relative abundance, whereas the other was little changed or significantly decreased in abundance. A common theme was an apparent increase in transcripts for functions using H(2) directly as reductant, versus those using the reduced deazaflavin (coenzyme F(420)). The greater importance of direct reduction by H(2) was supported by improved syntrophic growth of a deletion mutant in an F(420)-dependent dehydrogenase of M. maripaludis. These data suggest that paralogous genes enable the methanogen to adapt to changing substrate availability, sustaining it under environmental conditions that are often near the thermodynamic threshold for growth. Additionally, the discovery of interspecies alanine transfer adds another metabolic dimension to this environmentally relevant mutualism

Fixed-target serial crystallography at the Structural Biology Center

Serial synchrotron crystallography enables the study of protein structures under physiological temperature and reduced radiation damage by collection of data from thousands of crystals. The Structural Biology Center at Sector 19 of the Advanced Photon Source has implemented a fixed-target approach with a new 3D-printed mesh-holder optimized for sample handling. The holder immobilizes a crystal suspension or droplet emulsion on a nylon mesh, trapping and sealing a near-monolayer of crystals in its mother liquor between two thin Mylar films. Data can be rapidly collected in scan mode and analyzed in near real-time using piezoelectric linear stages assembled in an XYZ arrangement, controlled with a graphical user interface and analyzed using a high-performance computing pipeline. Here, the system was applied to two β-lactamases: a class D serine β-lactamase from Chitinophaga pinensis DSM 2588 and L1 metallo-β-lactamase from Stenotrophomonas maltophilia K279a

Chromosome landmarks and autosome-sex chromosome translocations in Rumex hastatulus, a plant with XX/XY1Y2 sex chromosome system

Rumex hastatulus is the North American endemic dioecious plant with heteromorphic sex chromosomes. It is differentiated into two chromosomal races: Texas (T) race characterised by a simple XX/XY sex chromosome system and North Carolina (NC) race with a polymorphic XX/XY1Y2 sex chromosome system. The gross karyotype morphology in NC race resembles the derived type, but chromosomal changes that occurred during its evolution are poorly understood. Our C-banding/DAPI and fluorescence in situ hybridization (FISH) experiments demonstrated that Y chromosomes of both races are enriched in DAPI-positive sequences and that the emergence of polymorphic sex chromosome system was accompanied by the break of ancestral Y chromosome and switch in the localization of 5S rDNA, from autosomes to sex chromosomes (X and Y2). Two contrasting domains were detected within North Carolina Y chromosomes: the older, highly heterochromatinised, inherited from the original Y chromosome and the younger, euchromatic, representing translocated autosomal material. The flow-cytometric DNA estimation showed ∼3.5 % genome downsizing in the North Carolina race. Our results are in contradiction to earlier reports on the lack of heterochromatin within Y chromosomes of this species and enable unambiguous identification of autosomes involved in the autosome-heterosome translocation, providing useful chromosome landmarks for further studies on the karyotype and sex chromosome differentiation in this species

KG-COVID-19: A Framework to Produce Customized Knowledge Graphs for COVID-19 Response.

Integrated, up-to-date data about SARS-CoV-2 and COVID-19 is crucial for the ongoing response to the COVID-19 pandemic by the biomedical research community. While rich biological knowledge exists for SARS-CoV-2 and related viruses (SARS-CoV, MERS-CoV), integrating this knowledge is difficult and time-consuming, since much of it is in siloed databases or in textual format. Furthermore, the data required by the research community vary drastically for different tasks; the optimal data for a machine learning task, for example, is much different from the data used to populate a browsable user interface for clinicians. To address these challenges, we created KG-COVID-19, a flexible framework that ingests and integrates heterogeneous biomedical data to produce knowledge graphs (KGs), and applied it to create a KG for COVID-19 response. This KG framework also can be applied to other problems in which siloed biomedical data must be quickly integrated for different research applications, including future pandemics

MicrobesOnline: an integrated portal for comparative and functional genomics

Since 2003, MicrobesOnline (http://www.microbesonline.org) has been providing a community resource for comparative and functional genome analysis. The portal includes over 1000 complete genomes of bacteria, archaea and fungi and thousands of expression microarrays from diverse organisms ranging from model organisms such as Escherichia coli and Saccharomyces cerevisiae to environmental microbes such as Desulfovibrio vulgaris and Shewanella oneidensis. To assist in annotating genes and in reconstructing their evolutionary history, MicrobesOnline includes a comparative genome browser based on phylogenetic trees for every gene family as well as a species tree. To identify co-regulated genes, MicrobesOnline can search for genes based on their expression profile, and provides tools for identifying regulatory motifs and seeing if they are conserved. MicrobesOnline also includes fast phylogenetic profile searches, comparative views of metabolic pathways, operon predictions, a workbench for sequence analysis and integration with RegTransBase and other microbial genome resources. The next update of MicrobesOnline will contain significant new functionality, including comparative analysis of metagenomic sequence data. Programmatic access to the database, along with source code and documentation, is available at http://microbesonline.org/programmers.html.United States. Dept. of Energy (Genomics: GTL program (grant DE-AC02-05CH11231)

KG-Hub-building and exchanging biological knowledge graphs.

MOTIVATION: Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous data and making inferences in biology and many other domains, but a coherent solution for constructing, exchanging, and facilitating the downstream use of KGs is lacking. RESULTS: Here we present KG-Hub, a platform that enables standardized construction, exchange, and reuse of KGs. Features include a simple, modular extract-transform-load pattern for producing graphs compliant with Biolink Model (a high-level data model for standardizing biological data), easy integration of any OBO (Open Biological and Biomedical Ontologies) ontology, cached downloads of upstream data sources, versioned and automatically updated builds with stable URLs, web-browsable storage of KG artifacts on cloud infrastructure, and easy reuse of transformed subgraphs across projects. Current KG-Hub projects span use cases including COVID-19 research, drug repurposing, microbial-environmental interactions, and rare disease research. KG-Hub is equipped with tooling to easily analyze and manipulate KGs. KG-Hub is also tightly integrated with graph machine learning (ML) tools which allow automated graph ML, including node embeddings and training of models for link prediction and node classification. AVAILABILITY AND IMPLEMENTATION: https://kghub.org

Semantic integration of clinical laboratory tests from electronic health records for deep phenotyping and biomarker discovery.

Electronic Health Record (EHR) systems typically define laboratory test results using the Laboratory Observation Identifier Names and Codes (LOINC) and can transmit them using Fast Healthcare Interoperability Resource (FHIR) standards. LOINC has not yet been semantically integrated with computational resources for phenotype analysis. Here, we provide a method for mapping LOINC-encoded laboratory test results transmitted in FHIR standards to Human Phenotype Ontology (HPO) terms. We annotated the medical implications of 2923 commonly used laboratory tests with HPO terms. Using these annotations, our software assesses laboratory test results and converts each result into an HPO term. We validated our approach with EHR data from 15,681 patients with respiratory complaints and identified known biomarkers for asthma. Finally, we provide a freely available SMART on FHIR application that can be used within EHR systems. Our approach allows readily available laboratory tests in EHR to be reused for deep phenotyping and exploits the hierarchical structure of HPO to integrate distinct tests that have comparable medical interpretations for association studies

The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species.

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven’t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics