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bioRxiv2020

A meta-analysis of the inhibin network reveals prognostic value in multiple solid tumors

ABSTRACTInhibins and activins are dimeric ligands belonging to the TGFβ superfamily with emergent roles in cancer. Inhibins contain an α-subunit (INHA) and a β-subunit (either INHBA or INHBB), while activins are mainly homodimers of either βA (INHBA) or βB (INHBB) subunits. Inhibins are biomarkers in a subset of cancers and utilize the coreceptors betaglycan (TGFBR3) and endoglin (ENG) for physiological or pathological outcomes. Given the array of prior reports on inhibin, activin and the coreceptors in cancer, this study aims to provide a comprehensive analysis, assessing their functional prognostic potential in cancer using a bioinformatics approach. We identify cancer cell lines and cancer types most dependent and impacted, which included p53 mutated breast and ovarian cancers and lung adenocarcinomas. Moreover, INHA itself was dependent on TGFBR3 and ENG in multiple cancer types. INHA, INHBA, TGFBR3, and ENG also predicted patients’ response to anthracycline and taxane therapy in luminal A breast cancers. We also obtained a gene signature model that could accurately classify 96.7% of the cases based on outcomes. Lastly, we cross-compared gene correlations revealing INHA dependency to TGFBR3 or ENG influencing different pathways themselves. These results suggest that inhibins are particularly important in a subset of cancers depending on the coreceptor TGFBR3 and ENG and are of substantial prognostic value, thereby warranting further investigation.Competing Interest StatementThe authors have declared no competing interest.View Full Text

cancer biology↗

bioRxiv2020

Virus-Receptor Interactions of Glycosylated SARS-CoV-2 Spike and Human ACE2 Receptor

The current COVID-19 pandemic is caused by the SARS-CoV-2 betacoronavirus, which utilizes its highly glycosylated trimeric Spike protein to bind to the cell surface receptor ACE2 glycoprotein and facilitate host cell entry. We utilized glycomics-informed glycoproteomics to characterize site-specific microheterogeneity of glycosylation for a recombinant trimer Spike mimetic immunogen and for a soluble version of human ACE2. We combined this information with bioinformatic analyses of natural variants and with existing 3D-structures of both glycoproteins to generate molecular dynamics simulations of each glycoprotein alone and interacting with one another. Our results highlight roles for glycans in sterically masking polypeptide epitopes and directly modulating Spike-ACE2 interactions. Furthermore, our results illustrate the impact of viral evolution and divergence on Spike glycosylation, as well as the influence of natural variants on ACE2 receptor glycosylation that, taken together, can facilitate immunogen design to achieve antibody neutralization and inform therapeutic strategies to inhibit viral infection.

biochemistry↗

bioRxiv2020

A new subclass of exoribonuclease resistant RNA found in multiple Flaviviridae genera

Viruses have developed innovative strategies to exploit the cellular machinery and overcome the host antiviral defenses, often using specifically structured RNA elements. Examples are found in flaviviruses; during flaviviral infection, pathogenic subgenomic flaviviral RNAs (sfRNAs) accumulate in the cell. These sfRNAs are formed when a host cell 5 to 3 exoribonuclease degrades the viral genomic RNA but is blocked by an exoribonuclease resistant RNA structure (xrRNA) located in the viral genomes 3untranslated region (UTR). Although known to exist in several Flaviviridae genera the full distribution and diversity of xRNAs in this virus family was unknown. Using the recent high-resolution structure of an xrRNA from the divergent flavivirus Tamana bat virus (TABV) as a reference, we used bioinformatic searches to identify xrRNA in the Pegivirus, Pestivirus, and Hepacivirus genera. We biochemically and structurally characterized several examples, determining that they are genuine xrRNAs with a conserved fold. These new xrRNAs look superficially similar to the previously described xrRNAs but possess structural differences making them distinct from previous classes of xrRNAs. Our findings thus require adjustments of previous xrRNA classification schemes and expand on the previously known distribution of the xrRNA in Flaviviridae, indicating their widespread distribution and illustrating their importance. IMPORTANCEThe Flaviviridae comprise one of the largest families of positive sense single stranded (+ssRNA) and it is divided into the Flavivirus, Pestivirus, Pegivirus, and Hepacivirus genera. The genus Flavivirus contains many medically relevant viruses such as Zika Virus, Dengue Virus, and Powassan Virus. In these, a part of the viruss RNA twists up into a very special three-dimensional shape called an xrRNA that blocks the ability of the cell to "chew up" the viral RNA. Hence, part of the virus RNA remains intact, and this protected part is important for viral infection. This was known to occur in Flaviviruses but whether it existed in the other members of the family was not known. In this study, we not only identified a new subclass of xrRNA found in Flavivirus but also in the remaining three genera. The fact that this process of viral RNA maturation exists throughout the entire Flaviviridae family makes it clear that this is an important but underappreciated part of the infection strategy of these diverse human pathogens.

microbiology↗

bioRxiv2020

Food-Poisoning Bacteria Employ a Citrate Synthase and a Type II NRPS to Synthesize Bolaamphiphilic Lipopeptide Antibiotics

Mining the genome of the food-spoiling bacterium Burkholderia gladioli pv. cocovenenans revealed five non-ribosomal peptide synthetase (NRPS) gene clusters, including an orphan gene locus (bol). Gene inactivation and metabolic profiling linked the bol gene cluster to novel bolaamphiphilic lipopeptides with antimycobacterial activity. A combination of chemical analyses and bioinformatics elucidated the structures of bolagladin A and B, lipocyclopeptides featuring an unusual dehydro-{beta}-alanine enamide linker fused to an unprecedented tricarboxylic fatty acid tail. Through a series of targeted gene deletions we proved the involvement of a designated citrate synthase (CS), priming ketosynthases (KS III), a type II NRPS including a novel desaturase for enamide formation, and a multimodular NRPS generating the cyclopeptide. Network analyses revealed the evolutionary origin of the CS and identified cryptic CS/NRPS gene loci in various bacterial genomes.

microbiology↗

bioRxiv2020

Deglutarylation of GCDH by SIRT5 controls lysine metabolism in mice

ABSTRACTA wide range of protein acyl modifications has been identified on enzymes across various metabolic processes; however, the impact of these modifications remains poorly understood. Protein glutarylation is a recently identified modification that can be non-enzymatically driven by glutaryl-CoA. In mammalian systems, this unique metabolite is only produced in the lysine and tryptophan oxidative pathways. To better understand the biology of protein glutarylation, we studied the relationship between enzymes within the lysine/tryptophan catabolic pathways, protein glutarylation, and regulation by the deglutarylating enzyme Sirtuin 5 (SIRT5). Here, we identify glutarylation on the lysine oxidation pathway enzyme glutaryl-CoA dehydrogenase (GCDH). We show increased GCDH glutarylation when glutaryl-CoA production is stimulated by lysine catabolism. Our data reveal glutarylation of GCDH impacts its function, ultimately decreasing lysine oxidation. We then demonstrate the ability of SIRT5 to deglutarylate GCDH, restoring its enzymatic activity. Finally, metabolomic and bioinformatic analyses indicate an expanded role for SIRT5 in regulating amino acid metabolism. Together, these data support a model whereby a feedback loop exists within the lysine/tryptophan oxidation pathway, in which glutaryl-CoA is produced, in turn inhibiting GCDH function via glutaryl modification of GCDH lysine residues, and can be relieved by SIRT5 deacylation activity.View Full Text

biochemistry↗

bioRxiv2020

Next-generation diagnostics: virus capture facilitates a sensitive viral diagnosis for epizootic and zoonotic pathogens including SARS-CoV-2

BackgroundThe detection of pathogens in clinical and environmental samples using high-throughput sequencing (HTS) is often hampered by large amounts of background information, which is especially true for viruses with small genomes. Enormous sequencing depth can be necessary to compile sufficient information for identification of a certain pathogen. Generic HTS combining with in-solution capture enrichment can markedly increase the sensitivity for virus detection in complex diagnostic samples. MethodsA virus panel based on the principle of biotinylated RNA-baits was developed for specific capture enrichment of epizootic and zoonotic viruses (VirBaits). The VirBaits set was supplemented by a SARS-CoV-2 predesigned bait set for testing recent SARS-CoV-2 positive samples. Libraries generated from complex samples were sequenced via generic HTS and afterwards enriched with the VirBaits set. For validation, an internal proficiency test for emerging epizootic and zoonotic viruses (African swine fever virus, Ebolavirus, Marburgvirus, Nipah henipavirus, Rift Valley fever virus) was conducted. ResultsThe VirBaits set consists of 177,471 RNA-baits (80-mer) based on about 18,800 complete viral genomes targeting 35 epizootic and zoonotic viruses. In all tested samples, viruses with both DNA and RNA genomes were clearly enriched ranging from about 10-fold to 10,000-fold for viruses including distantly related viruses with at least 72% overall identity to viruses represented in the bait set. Viruses showing a lower overall identity (38% and 46%) to them were not enriched but could nonetheless be detected based on capturing conserved genome regions. The internal proficiency test supports the improved virus detection using the combination of HTS plus targeted enrichment but also point to the risk of carryover between samples. ConclusionsThe VirBaits approach showed a high diagnostic performance, also for distantly related viruses. The bait set is modular and expandable according to the favored diagnostics, health sector or research question. The risk of carryover needs to be taken into consideration. The application of the RNA-baits principle turned out to be user-friendly, and even non-experts (without sophisticated bioinformatics skills) can easily use the VirBait workflow. The rapid extension of the established VirBaits set adapted to actual outbreak events is possible without any problems as shown for SARS-CoV-2.

genomics↗

bioRxiv2020

Predictive Metabolic Pathways of Lactic Acid Bacterial Strains Isolated from Fermented Foods

We attempted to use PICTRUSt2 software and bioinformatics tool to infer the raw sequences obtained from pure strains of Lactococcus lactis and Lactobacillus plantarum isolated from some fermented foods in India, which were identified by 16S rRNA gene sequencing method. Predictive metabolic pathways of 16S sequences of LAB strains were predicted by PICRUSt2 mapped against KEGG database, which showed genes associated with metabolism (36.74%), environmental information processing (32.34%), genetic information processing (9.86%) and the unclassified (21.06%). KGGE database also showed the dominant genes related to predictive sub-pathways of metabolism at level-2 were membrane transport (31.16%) and carbohydrate metabolism (12.42%).

microbiology↗

bioRxiv2020

In vivo phage display: identification of organ-specific peptides using deep sequencing and differential profiling across tissues

In vivo phage display is widely used for identification of organ- or disease-specific homing peptides. However, the current in vivo phage biopanning approaches fail to assess biodistribution of specific peptide phages across tissues during the screen, thus necessitating laborious and time-consuming post-screening validation studies on individual peptide phages. Here, we adopted bioinformatics tools used for RNA sequencing for analysis of high throughput sequencing (HTS) data to estimate the representation of individual peptides during biopanning in vivo. The data from in vivo phage screen were analyzed using differential binding - relative representation of each peptide in the target organ vs. in a panel of control organs. Application of this approach in a model study using low-diversity peptide T7 phage library with spiked-in brain homing phage, demonstrated brain-specific differential binding of brain homing phage and resulted in identification of novel lung and brain specific homing peptides. Our study provides a broadly applicable approach to streamline in vivo peptide phage biopanning and to increase its reproducibility and success rate. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=90 SRC="FIGDIR/small/181974v2_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@1853e75org.highwire.dtl.DTLVardef@c7ad8corg.highwire.dtl.DTLVardef@152f4feorg.highwire.dtl.DTLVardef@15261d0_HPS_FORMAT_FIGEXP M_FIG C_FIG In vivo phage display using differential binding approach

molecular biology↗

bioRxiv2020

An evolutionary approach to systematic discovery of novel deubiquitinases, applied to Legionella

Deubiquitinating enzymes (DUBs) are important regulators of the posttranslational protein ubiquitination system. Mammalian genomes encode about hundred different DUBs, which can be grouped into seven different classes. Members of other DUB classes are found in pathogenic bacteria, which use them to target the host defense. By combining bioinformatical and experimental approaches, we address the question if the known DUB families have a common evolutionary ancestry and share conserved features that set them apart from other proteases. By systematically comparing family-specific Hidden-Markov-Models, we uncovered distant relationships between established DUBs and other cysteine protease families. Most DUB families share a conserved aromatic residue linked to the active site, which restricts the cleavage of substrates with sidechains at the S2 position, corresponding to Gly-75 in ubiquitin. By applying these criteria to Legionella pneumophila ORFs, we identified lpg1621 and lpg1148 as deubiquitinases, characterized their cleavage specificities, and confirmed the importance of the aromatic gatekeeper motif for substrate selection.Competing Interest StatementThe authors have declared no competing interest.View Full Text

biochemistry↗

bioRxiv2020

Non-allelic homologous recombination of Alu and LINE-1 elements generates somatic complexity in human genomes.

Millions of Alu and L1 copies in our genomes contribute to evolution and genetic disorders via non-allelic homologous recombination, but the somatic extent of these rearrangements has not been systematically investigated. Here we combine short and long DNA reads sequencing of repeat elements with a new bioinformatic pipeline to show that somatic recombination of Alu and L1 elements is common in human genomes. We report new tissue-specific recombination hallmarks, and show that retroelements acting as recombination hotspots are enriched in centromeres and cancer genes. We compare recombination profiles in human induced pluripotent stem cells and differentiated neurons and show that neuron-specific recombination of repeat elements accompanies chromatin changes during cell-fate determination. Finally, we find that somatic recombination profiles are altered in Parkinsons and Alzheimers disease, indicating a link between retroelements recombination and genomic instability in neurodegeneration. This work shows that somatic recombination of repeat elements contributes massively to genomic diversity in health and disease.

genomics↗

bioRxiv2020

Metagenome-assembled genomes from Monte Cristo Cave (Diamantina, Brazil) reveal prokaryotic lineages as functional models for life on Mars

Although several studies have explored microbial communities in different terrestrial subsurface ecosystems, little is known about the diversity of their metabolic processes and survival strategies. The advance of bioinformatic tools is allowing the description of novel and not-yet cultivated microbial lineages in different ecosystems, due to the genome reconstruction approach from metagenomic data. The recovery of genomes has the potential of revealing novel lifestyles, metabolic processes and ecological roles of microorganisms, mainly in ecosystems that are largely unknown, and in which cultivation could be not viable. In this study, through shotgun metagenomic data, it was possible to reconstruct several genomes of cultivated and not-yet cultivated prokaryotic lineages from a quartzite cave, located in Minas Gerais state, Brazil, which showed to possess a high diversity of genes involved with different biogeochemical cycles, including reductive and oxidative pathways related to carbon, sulfur, nitrogen and iron. Tree genomes were selected, assigned as Truepera sp., Ca. Methylomirabilis sp. and Ca. Koribacter sp. based on their lifestyles (radiation resistance, anaerobic methane oxidation and potential iron oxidation) for pangenomic analysis, which exhibited genes involved with different DNA repair strategies, starvation and stress response. Since these groups have few reference genomes deposited in databases, our study adds important genomic information about these lineages. The combination of techniques applied in this study allowed us to unveil the potential relationships between microbial genomes and their ecological processes with the cave mineralogy, as well as to discuss their implications for the search for extant lifeforms outside our planet, in silica- and iron-rich environments, especially on Mars.

microbiology↗

bioRxiv2020

A global resource for genomic predictions of antimicrobial resistance and surveillance of Salmonella Typhi at Pathogenwatch

BackgroundMicrobial whole-genome sequencing (WGS) is now increasingly used to inform public health investigations of infectious disease. This approach has transformed our understanding of the global population structure of Salmonella enterica serovar Typhi (S. Typhi), the causative agent of typhoid fever. WGS has been particularly informative for understanding the global spread of multi-drug resistant (MDR) typhoid. As WGS capacity becomes more decentralised, there is a growing opportunity for collaboration and sharing of surveillance data within and between countries to inform disease control policies. This requires freely available, community driven tools that reduce the barriers to access genomic data for public health surveillance and that deliver genomic data on a global scale. MethodsHere we present the Pathogenwatch (https://pathogen.watch/styphi) scheme for S. Typhi, a web application enabling the rapid identification of genomic markers of antimicrobial resistance (AMR) and contextualization with public genomic data to identify high-risk clones at a population level. Data are delivered in single genome reports or in collections of genomes combined with geographic and other data using trees, maps and tables. ResultsWe show that the clustering of S. Typhi genomes in Pathogenwatch is comparable to established bioinformatics methods, and that genomic predictions of AMR are largely concordant with phenotypic drug susceptibility data. We demonstrate the public health utility of Pathogenwatch with examples selected from over 4,300 public genomes available in the application. ConclusionsPathogenwatch democratises genomic epidemiology of S. Typhi by providing an intuitive entry point for the analysis of WGS and linked epidemiological data, enabling international public health monitoring of the emergence and spread of high risk clones.

genomics↗

bioRxiv2020

VIRIDIC - a novel tool to calculate the intergenomic similarities of prokaryote-infecting viruses

Nucleotide based intergenomic similarities are useful to understand how viruses are related with each other and to classify them. Here we have developed VIRIDIC, which implements the traditional algorithm used by the International Committee on Taxonomy of Viruses (ICTV), Bacterial and Archaeal Viruses Subcommittee, to calculate virus intergenomic similarities. When compared with other software, VIRIDIC gave the best agreement with the traditional algorithm. Furthermore, it proved best at estimating the relatedness between more distantly related phages, relatedness that other tools can significantly overestimate. In addition to the intergenomic similarities, VIRIDIC also calculates three indicators of the alignment ability to capture the relatedness between viruses: the aligned fractions for each genome in a pair and the length ratio between the two genomes. The main output of VIRIDIC is a heatmap integrating the intergenomic similarity values with information regarding the genome lengths and the aligned genome fraction. VIRIDIC is available at viridic.icbm.de, both as a web-service and a stand-alone tool. It allows fast analysis of large phage genome datasets, especially in the stand-alone version, which can be run on the user’s own servers and can be integrated in bioinformatics pipelines. VIRIDIC was developed having viruses of Bacteria and Archaea in mind, however, it could potentially be used for eukaryotic viruses as well, as long as they are monopartite.Competing Interest StatementThe authors have declared no competing interest.View Full Text

microbiology↗

bioRxiv2020

PaintSHOP enables the interactive design of transcriptome- and genome-scale oligonucleotide FISH experiments

Fluorescent in situ hybridization (FISH) allows researchers to visualize the spatial position and quantity of nucleic acids in fixed samples. Recently, considerable progress has been made in developing oligonucleotide (oligo)-based FISH methods. These methods have enabled researchers to study the three-dimensional organization of the genome at super-resolution and visualize the spatial patterns of gene expression for thousands of genes in individual cells. While considerable progress has been made in developing new molecular methods that harness complex oligo libraries for FISH, there are few existing computational tools to support the bioinformatics workflows necessary to carry out these experiments. Here, we introduce Paint Server and Homology Optimization Pipeline (PaintSHOP), an interactive platform for the reproducible design of oligo FISH experiments. PaintSHOP enables researchers to identify probes for their experimental targets efficiently, to incorporate additional necessary sequences such as primer pairs, and to easily generate standardized files documenting the design of their libraries. Our platform integrates a machine learning model that quantitatively predicts probe specificity on the genome scale into a dynamic web application that creates ready-to-order probe sets for a wide variety of applications. The goal of this freely available web resource is to democratize and standardize the process of designing complex probe sets for the oligo FISH community. PaintSHOP can be accessed at: paintshop.ioCompeting Interest StatementThe authors have declared no competing interest.View Full Text

genomics↗

bioRxiv2020

Gene Expression Network Analysis Provides Potential Targets Against SARS-CoV-2

ABSTRACTBACKGROUND Cell entry of SARS-CoV-2, the novel coronavirus causing COVID-19, is facilitated by host cell angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2). We aimed to identify and characterize genes that are co-expressed with ACE2 and TMPRSS2, and to further explore their biological functions and potential as druggable targets.METHODS Using the gene expression profiles of 1,038 lung tissue samples, we performed a weighted gene correlation network analysis (WGCNA) to identify modules of co-expressed genes. We explored the biology of co-expressed genes using bioinformatics databases, and identified known drug-gene interactions.RESULTS ACE2 was in a module of 681 co-expressed genes; 12 genes with moderate-high correlation with ACE2 (r>0.3, FDR<0.05) had known interactions with existing drug compounds. TMPRSS2 was in a module of 1,086 co-expressed genes; 15 of these genes were enriched in the gene ontology biologic process ‘Entry into host cell’, and 53 TMPRSS2-correlated genes had known interactions with drug compounds.CONCLUSION Dozens of genes are co-expressed with ACE2 and TMPRSS2, many of which have plausible links to COVID-19 pathophysiology. Many of the co-expressed genes are potentially targetable with existing drugs, which may help to fast-track the development of COVID-19 therapeutics.Competing Interest StatementS.M. reports personal fees from Novartis and Boehringer-Ingelheim, outside the submitted work. W.T. reports fees to Institution from Roche-Ventana, AbbVie, Merck-Sharp-Dohme and Bristol-Myers-Squibb, outside the submitted work. M.B. reports research grants paid to University from Astra Zeneca, Novartis, outside the submitted work. D.D.S. reports research funding from AstraZeneca and received honoraria for speaking engagements from Boehringer Ingelheim and AstraZeneca over the past 36 months, outside of the submitted work.View Full Text

genomics↗

bioRxiv2020

A Small interfering RNA lead targeting RNA-dependent RNA-polymerase effectively inhibit the SARS-CoV-2 infection in Golden Syrian hamster and Rhesus macaque

A small interfering RNA (siRNA) inhibitors have demonstrated the novel modality for suppressing infectious diseases. Sixty-one siRNA molecules, predicted by the bioinformatics programs, were screened for the possibility of treating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using an in vitro plaque assay. Among six siRNA leads with the efficacy of reducing plaque number, the siRNA targeting RNA-dependent RNA polymerase (RdRp) showed a reduction in SARS-CoV-2 infection-induced fever and virus titer in the Golden Syrian hamster and rhesus macaque. These results suggest the potential for RdRp targeting siRNA as a new treatment for the coronavirus disease 2019 (COVID-19).Competing Interest StatementThe authors have declared no competing interest.View Full Text

microbiology↗

bioRxiv2020

Metabolic fate of human immunoactive sterols in Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) infection is among top ten causes of death worldwide, and the number of drug-resistant strains is increasing. The direct interception of human immune signaling molecules by Mtb remains elusive, limiting drug discovery. Oxysterols and secosteroids regulate both innate and adaptive immune responses. Here we report a functional, structural, and bioinformatics study of Mtb enzymes initiating cholesterol catabolism and demonstrated their interrelation with human immunity. We show that these enzymes metabolize human immune oxysterol messengers. Rv2266, the most potent among them, can also metabolize vitamin D3 (VD3) derivatives. High-resolution structures show common patterns of sterols binding and reveal a site for oxidative attack during catalysis. Finally, we designed a compound that binds and inhibits three studied proteins. The compound shows activity against Mtb H37Rv residing in macrophages. Our findings contribute to molecular understanding of suppression of immunity and suggest that Mtb has its own transformation system resembling the human phase I drug-metabolizing system.Competing Interest StatementA.Gi. and E.S. are employees of MT-Medicals LLC. The other authors declare no competing interests.View Full Text

biochemistry↗

bioRxiv2020

Sensitive and reproducible determination of clinical HDL proteotypes

BackgroundHigh-density lipoprotein (HDL) is a heterogenous mixture of blood-circulating multimolecular particles containing many different proteins, lipids, and RNAs. Recent advancements in mass spectrometry-based proteotype analysis strategies enable the sensitive and reproducible quantification of proteins across large patient cohorts. MethodsHDL particles were isolated from plasma of more than 300 healthy individuals or patients with a multiplicity of physiological HDL states. From these, peptides were extracted and HDL proteome spectral libraries were generated. This is a prerequisite for using data-independent acquisition (DIA) strategies to analyze HDL particles from clinical cohorts using mass spectrometry. ResultsThe resulting HDL proteome spectral libraries consist of 296 protein groups and 341 peptidoforms of potential biological significance identified with high confidence. We used the HDL proteome libraries to evaluate HDL proteotype differences in between healthy individuals and patients suffering from diabetes mellitus type 2 (T2DM) and/or coronary heart disease (CHD). Bioinformatic interrogation of the data revealed significant quantitative differences in the HDL proteotypes including a significant depletion of phosphatidylinositol-glycan-specific phospholipase D (PHLD) from disease-derived HDL particles. ConclusionThe DIA-based HDL proteotyping strategy enabled sensitive and reproducible digitization of HDL proteotypes derived from patient cohorts and provides new insights into the composition of HDL particles as a rational basis to decode structure-function-disease relationships of HDL. List of human genes and protein names discussed in the paper- APOA1 (Apolipoprotein A-I) - APOA2 (Apolipoprotein A-II) - APOE (Apolipoprotein E) - APOC3 (Apolipoprotein C3) - CLUS (Clusterin) - PHLD (Phosphatidylinositol-glycan-specific phospholipase D) - PON1 (Serum paraoxonase/arylesterase 1) - PON3 (Serum paraoxonase/lactonase 3) - PSPB (Pulmonary surfactant-associated protein B) - RAB1B (Ras-related protein Rab-1B) - RAB6A (Ras-related protein Rab-6A) - RB11A/B (Ras-related protein Rab-11A/B) - RP1BL (Ras-related protein Rap-1b-like protein) - RAB10 (Ras-related protein Rab-10) - SAA1 (Serum amyloid A-1 protein) - SAA2 (Serum amyloid A-2 protein) - SAA4 (Serum amyloid A-4 protein) - SCRB1 (Scavenger receptor class B member 1)

molecular biology↗