Molecular Insights of Cholestasis in MDR2 Knockout Murine Liver Organoids.

MDR3 (multidrug resistance 3) deficiency in humans (MDR2 in mice) causes progressive familial intrahepatic cholestasis type 3 (PFIC3). PFIC3 is a lethal disease characterized by an early onset of intrahepatic cholestasis progressing to liver cirrhosis, a preneoplastic condition, putting individuals at risk of hepatocellular carcinoma (HCC). Hepatocyte-like organoids from MDR2-deficient mice (MDR2KO) were used in this work to study the molecular alterations caused by the deficiency of this transporter. Proteomic analysis by mass spectrometry allowed characterization of 279 proteins that were differentially expressed in MDR2KO compared with wild-type organoids. Functional enrichment analysis indicated alterations in three main cellular functions: (1) interaction with the extracellular matrix, (2) remodeling intermediary metabolism, and (3) cell proliferation and differentiation. The affected cellular processes were validated by orthogonal molecular biology techniques. Our results point to molecular mechanisms associated with PFIC3 that may drive the progression to liver cirrhosis and HCC and suggest proteins and cellular processes that could be targeted for the development of early detection strategies for these severe liver diseases.

Proteomic snapshot of saliva samples predicts new pathways implicated in SARS-CoV-2 pathogenesis.

BACKGROUND: Information on the microbiome's human pathways and active members that can affect SARS-CoV-2 susceptibility and pathogenesis in the salivary proteome is very scarce. Here, we studied a unique collection of samples harvested from April to June 2020 from unvaccinated patients. METHODS: We compared 10 infected and hospitalized patients with severe (n = 5) and moderate (n = 5) coronavirus disease (COVID-19) with 10 uninfected individuals, including non-COVID-19 but susceptible individuals (n = 5) and non-COVID-19 and nonsusceptible healthcare workers with repeated high-risk exposures (n = 5). RESULTS: By performing high-throughput proteomic profiling in saliva samples, we detected 226 unique differentially expressed (DE) human proteins between groups (q-value ≤ 0.05) out of 3376 unambiguously identified proteins (false discovery rate ≤ 1%). Major differences were observed between the non-COVID-19 and nonsusceptible groups. Bioinformatics analysis of DE proteins revealed human proteomic signatures related to inflammatory responses, central cellular processes, and antiviral activity associated with the saliva of SARS-CoV-2-infected patients (p-value ≤ 0.0004). Discriminatory biomarker signatures from human saliva include cystatins, protective molecules present in the oral cavity, calprotectins, involved in cell cycle progression, and histones, related to nucleosome functions. The expression levels of two human proteins related to protein transport in the cytoplasm, DYNC1 (p-value, 0.0021) and MAPRE1 (p-value, 0.047), correlated with angiotensin-converting enzyme 2 (ACE2) plasma activity. Finally, the proteomes of microorganisms present in the saliva samples showed 4 main microbial functional features related to ribosome functioning that were overrepresented in the infected group. CONCLUSION: Our study explores potential candidates involved in pathways implicated in SARS-CoV-2 susceptibility, although further studies in larger cohorts will be necessary.

Discrimination of Etiologically Different Cholestasis by Modeling Proteomics Datasets.

Cholestasis is characterized by disrupted bile flow from the liver to the small intestine. Although etiologically different cholestasis displays similar symptoms, diverse factors can contribute to the progression of the disease and determine the appropriate therapeutic option. Therefore, stratifying cholestatic patients is essential for the development of tailor-made treatment strategies. Here, we have analyzed the liver proteome from cholestatic patients of different etiology. In total, 7161 proteins were identified and quantified, of which 263 were differentially expressed between control and cholestasis groups. These differential proteins point to deregulated cellular processes that explain part of the molecular framework of cholestasis progression. However, the clustering of different cholestasis types was limited. Therefore, a machine learning pipeline was designed to identify a panel of 20 differential proteins that segregate different cholestasis groups with high accuracy and sensitivity. In summary, proteomics combined with machine learning algorithms provides valuable insights into the molecular mechanisms of cholestasis progression and a panel of proteins to discriminate across different types of cholestasis. This strategy may prove useful in developing precision medicine approaches for patient care.

Proteomic Serum Profiling of Holstein Friesian Cows with Different Pathological Forms of Bovine Paratuberculosis Reveals Changes in the Acute-Phase Response and Lipid Metabolism.

The lack of sensitive diagnostic methods to detect Mycobacterium avium subsp. paratuberculosis (Map) subclinical infections has hindered the control of paratuberculosis (PTB). The serum proteomic profiles of naturally infected cows presenting focal and diffuse pathological forms of PTB and negative controls (n = 4 per group) were analyzed using TMT-6plex quantitative proteomics. Focal and diffuse are the most frequent pathological forms in subclinical and clinical stages of PTB, respectively. One (focal versus (vs.) control), eight (diffuse vs. control), and four (focal vs. diffuse) differentially abundant (DA) proteins (q-value < 0.05) were identified. Ingenuity pathway analysis of the DA proteins revealed changes in the acute-phase response and lipid metabolism. Six candidate biomarkers were selected for further validation by specific ELISA using serum from animals with focal, multifocal, and diffuse PTB-associated lesions (n = 108) and controls (n = 56). Overall, the trends of the serum expression levels of the selected proteins were consistent with the proteomic results. Alpha-1-acid glycoprotein (ORM1)-based ELISA, insulin-like growth factor-binding protein 2 (IGFBP2)-based ELISA, and the anti-Map ELISA had the best diagnostic performance for detection of animals with focal, multifocal, and diffuse lesions, respectively. Our findings identify potential biomarkers that improve diagnostic sensitivity of PTB and help to elucidate the mechanisms involved in PTB pathogenesis.

Identification and experimental validation of druggable epigenetic targets in hepatoblastoma.

BACKGROUND & AIMS: Hepatoblastoma (HB) is the most frequent childhood liver cancer. Patients with aggressive tumors have limited therapeutic options; therefore, a better understanding of HB pathogenesis is needed to improve treatment. HBs have a very low mutational burden; however, epigenetic alterations are increasingly recognized. We aimed to identify epigenetic regulators consistently dysregulated in HB and to evaluate the therapeutic efficacy of their targeting in clinically relevant models. METHODS: We performed a comprehensive transcriptomic analysis of 180 epigenetic genes. Data from fetal, pediatric, adult, peritumoral (n = 72) and tumoral (n = 91) tissues were integrated. Selected epigenetic drugs were tested in HB cells. The most relevant epigenetic target identified was validated in primary HB cells, HB organoids, a patient-derived xenograft model, and a genetic mouse model. Transcriptomic, proteomic and metabolomic mechanistic analyses were performed. RESULTS: Altered expression of genes regulating DNA methylation and histone modifications was consistently observed in association with molecular and clinical features of poor prognosis. The histone methyltransferase G9a was markedly upregulated in tumors with epigenetic and transcriptomic traits of increased malignancy. Pharmacological targeting of G9a significantly inhibited growth of HB cells, organoids and patient-derived xenografts. Development of HB induced by oncogenic forms of ß-catenin and YAP1 was ablated in mice with hepatocyte-specific deletion of G9a. We observed that HBs undergo significant transcriptional rewiring in genes involved in amino acid metabolism and ribosomal biogenesis. G9a inhibition counteracted these pro-tumorigenic adaptations. Mechanistically, G9a targeting potently repressed the expression of c-MYC and ATF4, master regulators of HB metabolic reprogramming. CONCLUSIONS: HBs display a profound dysregulation of the epigenetic machinery. Pharmacological targeting of key epigenetic effectors exposes metabolic vulnerabilities that can be leveraged to improve the treatment of these patients. IMPACT AND IMPLICATIONS: In spite of recent advances in the management of hepatoblastoma (HB), treatment resistance and drug toxicity are still major concerns. This systematic study reveals the remarkable dysregulation in the expression of epigenetic genes in HB tissues. Through pharmacological and genetic experimental approaches, we demonstrate that the histone-lysine-methyltransferase G9a is an excellent drug target in HB, which can also be harnessed to enhance the efficacy of chemotherapy. Furthermore, our study highlights the profound pro-tumorigenic metabolic rewiring of HB cells orchestrated by G9a in coordination with the c-MYC oncogene. From a broader perspective, our findings suggest that anti-G9a therapies may also be effective in other c-MYC-dependent tumors.

Eventos de vida estresantes y su efecto en la conducta suicida en mujeres durante la pandemia por Covid-19 en México.

OBJETIVO: Analizar la estructura factorial, la validez convergente y divergente de la Escala Columbia de Severidad Suicida (CSSRS) y el Cuestionario de Eventos de Vida Estresantes (EVE) y medir la asociación entre EVE y conducta suicida (CS) en mujeres mexicanas durante la pandemia por Covid-19. Material y métodos. Se usaron datos de 2 398 mujeres que participaron en un estudio multicéntrico, realizado en México entre mayo y octubre de 2021. La información se recolectó mediante un cuestionario en línea que incluyó la CSSRS y el EVE. Se hizo un análisis factorial confirmatorio para valorar el ajuste de los modelos. RESULTADOS: El modelo final mostró asociación entre los EVE y la CS, y tuvo a la violencia como variable central. Dicho modelo presentó un ajuste adecuado (CFI = 0.950, IFI = 0.950, MFI = 0.975, RMSEA = 0.031, CI RMSEA = 0.026-0.036). CONCLUSIONES: La pandemia por Covid-19 evidenció la necesidad de crear e implementar estrategias que promuevan el cuidado de la salud mental, reduzcan la exposición a la violencia y faciliten los procesos de duelo para prevenir la CS en mujeres mexicanas.

Splicing Factor SLU7 Prevents Oxidative Stress-Mediated Hepatocyte Nuclear Factor 4α Degradation, Preserving Hepatic Differentiation and Protecting From Liver Damage.

BACKGROUND AND AIMS: Hepatocellular dedifferentiation is emerging as an important determinant in liver disease progression. Preservation of mature hepatocyte identity relies on a set of key genes, predominantly the transcription factor hepatocyte nuclear factor 4α (HNF4α) but also splicing factors like SLU7. How these factors interact and become dysregulated and the impact of their impairment in driving liver disease are not fully understood. APPROACH AND RESULTS: Expression of SLU7 and that of the adult and oncofetal isoforms of HNF4α, driven by its promoter 1 (P1) and P2, respectively, was studied in diseased human and mouse livers. Hepatic function and damage response were analyzed in wild-type and Slu7-haploinsufficient/heterozygous (Slu7+/- ) mice undergoing chronic (CCl4 ) and acute (acetaminophen) injury. SLU7 expression was restored in CCl4 -injured mice using SLU7-expressing adeno-associated viruses (AAV-SLU7). The hepatocellular SLU7 interactome was characterized by mass spectrometry. Reduced SLU7 expression in human and mouse diseased livers correlated with a switch in HNF4α P1 to P2 usage. This response was reproduced in Slu7+/- mice, which displayed increased sensitivity to chronic and acute liver injury, enhanced oxidative stress, and marked impairment of hepatic functions. AAV-SLU7 infection prevented liver injury and hepatocellular dedifferentiation. Mechanistically we demonstrate a unique role for SLU7 in the preservation of HNF4α1 protein stability through its capacity to protect the liver against oxidative stress. SLU7 is herein identified as a key component of the stress granule proteome, an essential part of the cell's antioxidant machinery. CONCLUSIONS: Our results place SLU7 at the highest level of hepatocellular identity control, identifying SLU7 as a link between stress-protective mechanisms and liver differentiation. These findings emphasize the importance of the preservation of hepatic functions in the protection from liver injury.

Quantitative proteomic analysis of serum-purified exosomes identifies putative pre-eclampsia-associated biomarkers.

BACKGROUND: The high incidence of pre-eclampsia, which affects 2-7% of all pregnancies, remains a major health concern. Detection of pre-eclampsia before the appearance of clinical symptoms is essential to allow early intervention, and would benefit from identification of plasma/serum biomarkers to help guide diagnosis and treatment. Liquid biopsy has emerged as a promising source of protein biomarkers that circumvents some of the inherent challenges of proteome-wide analysis of plasma/serum. In this respect, purified exosomes have the added benefit of being carriers of intercellular communication both in physiological and pathological conditions. METHODS: We compared the protein complement of purified exosomes from three different collections of control and pre-eclamptic serum samples, obtained at the end of the second trimester of pregnancy and at delivery. We employed shotgun label-free proteomics to investigate differential protein expression, which was then validated by targeted proteomics. RESULTS: We developed a purification method that yielded highly enriched exosome preparations. The presence of specific pregnancy protein markers suggested that a significant proportion of purified exosomes derived from tissues related to pregnancy. Quantitative proteomic analyses allowed us to identify 10, 114 and 98 differentially-regulated proteins in the three sample collections, with a high degree of concordance. Functional analysis suggested that these proteins participate in biological processes related to pre-eclampsia, including angiogenesis, inflammation and cell migration. The differential abundance of 66 proteins was validated by targeted proteomics. Finally, we studied the impact of the pre-eclampsia-associated exosomes in the proteome using an in vitro cellular model. CONCLUSIONS: We have identified and validated differential exosomal proteins in liquid biopsy of pregnant women that open new possibilities for early detection of pre-eclampsia. Additionally, the functional impact of the proteome composition of purified pre-eclamptic exosomes in target cells provides new information to better understand changes in embryo-maternal interactions and, consequently, the pathogenesis of this disease.

Progress Identifying and Analyzing the Human Proteome: 2021 Metrics from the HUPO Human Proteome Project.

The 2021 Metrics of the HUPO Human Proteome Project (HPP) show that protein expression has now been credibly detected (neXtProt PE1 level) for 18 357 (92.8%) of the 19 778 predicted proteins coded in the human genome, a gain of 483 since 2020 from reports throughout the world reanalyzed by the HPP. Conversely, the number of neXtProt PE2, PE3, and PE4 missing proteins has been reduced by 478 to 1421. This represents remarkable progress on the proteome parts list. The utilization of proteomics in a broad array of biological and clinical studies likewise continues to expand with many important findings and effective integration with other omics platforms. We present highlights from the Immunopeptidomics, Glycoproteomics, Infectious Disease, Cardiovascular, Musculo-Skeletal, Liver, and Cancers B/D-HPP teams and from the Knowledgebase, Mass Spectrometry, Antibody Profiling, and Pathology resource pillars, as well as ethical considerations important to the clinical utilization of proteomics and protein biomarkers.

Quantitative proteomics-based analyses performed on pre-eclampsia samples in the 2004-2020 period: a systematic review.

BACKGROUND: Quantitative proteomics is an invaluable tool in biomedicine for the massive comparative analysis of protein component of complex biological samples. In the last two decades, this technique has been used to describe proteins potentially involved in the pathophysiological mechanisms of preeclampsia as well as to identify protein biomarkers that could be used with diagnostic/prognostic purposes in pre-eclampsia. RESULTS: We have done a systematic review of all proteomics-based papers describing differentially expressed proteins in this disease. Searching Pubmed with the terms pre-eclampsia and proteomics, restricted to the Title/Abstract and to MeSH fields, and following manual curation of the original list, retrieved 69 original articles corresponding to the 2004-2020 period. We have only considered those results based on quantitative, unbiased proteomics studies conducted in a controlled manner on a cohort of control and pre-eclamptic individuals. The sources of biological material used were serum/plasma (n = 32), placenta (n = 23), urine (n = 9), cerebrospinal fluid (n = 2), amniotic fluid (n = 2) and decidual tissue (n = 1). Overall results were filtered based on two complementary criteria. First, we have only accounted all those proteins described in at least two (urine), three (placenta) and four (serum/plasma) independent studies. Secondly, we considered the consistency of the quantitative data, that is, inter-study agreement in the protein abundance control/pre-eclamptic ratio. The total number of differential proteins in serum/plasma (n = 559), placenta (n = 912), urine (n = 132) and other sources of biological material (n = 26), reached 1631 proteins. Data were highly complementary among studies, resulting from differences on biological sources, sampling strategies, patient stratification, quantitative proteomic analysis methods and statistical data analysis. Therefore, stringent filtering was applied to end up with a cluster of 18, 29 and 16 proteins consistently regulated in pre-eclampsia in placenta, serum/plasma and urine, respectively. The systematic collection, standardization and evaluation of the results, using diverse filtering criteria, provided a panel of 63 proteins whose levels are consistently modified in the context of pre-eclampsia.

A Proteomic Approach for Systematic Mapping of Substrates of Human Deubiquitinating Enzymes.

The human genome contains nearly 100 deubiquitinating enzymes (DUBs) responsible for removing ubiquitin moieties from a large variety of substrates. Which DUBs are responsible for targeting which substrates remain mostly unknown. Here we implement the bioUb approach to identify DUB substrates in a systematic manner, combining gene silencing and proteomics analyses. Silencing of individual DUB enzymes is used to reduce their ubiquitin deconjugating activity, leading to an increase of the ubiquitination of their substrates, which can then be isolated and identified. We report here quantitative proteomic data of the putative substrates of 5 human DUBs. Furthermore, we have built a novel interactive database of DUB substrates to provide easy access to our data and collect DUB proteome data from other groups as a reference resource in the DUB substrates research field.

UPEFinder: A Bioinformatic Tool for the Study of Uncharacterized Proteins Based on Gene Expression Correlation and the PageRank Algorithm.

The Human Proteome Project (HPP) is leading the international effort to characterize the human proteome. Although the main goal of this project was first focused on the detection of missing proteins, a new challenge arose from the need to assign biological functions to the uncharacterized human proteins and describe their implications in human diseases. Not only the proteins with experimental evidence (uPE1 proteins) but also the uncharacterized missing proteins (uMPs) were the objects of study in this challenge, neXt-CP50. In this work, we developed a new bioinformatic approach to infer biological annotations for the uPE1 proteins and uMPs based on a "guilt-by-association" analysis using public RNA-Seq data sets. We used the correlation of these proteins with the well-characterized PE1 proteins to construct a network. In this way, we applied the PageRank algorithm to this network to identify the most relevant nodes, which were the biological annotations of the uncharacterized proteins. All of the generated information was stored in a database. In addition, we implemented the web application UPEFinder (https://upefinder.proteored.org) to facilitate the access to this new resource. This information is especially relevant for the researchers of the HPP who are interested in the generation and validation of new hypotheses about the functions of these proteins. Both the database and the web application are publicly available (https://github.com/ubioinformat/UPEfinder).

Research on the Human Proteome Reaches a Major Milestone: >90% of Predicted Human Proteins Now Credibly Detected, According to the HUPO Human Proteome Project.

According to the 2020 Metrics of the HUPO Human Proteome Project (HPP), expression has now been detected at the protein level for >90% of the 19 773 predicted proteins coded in the human genome. The HPP annually reports on progress made throughout the world toward credibly identifying and characterizing the complete human protein parts list and promoting proteomics as an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2020-01 classified 17 874 proteins as PE1, having strong protein-level evidence, up 180 from 17 694 one year earlier. These represent 90.4% of the 19 773 predicted coding genes (all PE1,2,3,4 proteins in neXtProt). Conversely, the number of neXtProt PE2,3,4 proteins, termed the "missing proteins" (MPs), was reduced by 230 from 2129 to 1899 since the neXtProt 2019-01 release. PeptideAtlas is the primary source of uniform reanalysis of raw mass spectrometry data for neXtProt, supplemented this year with extensive data from MassIVE. PeptideAtlas 2020-01 added 362 canonical proteins between 2019 and 2020 and MassIVE contributed 84 more, many of which converted PE1 entries based on non-MS evidence to the MS-based subgroup. The 19 Biology and Disease-driven B/D-HPP teams continue to pursue the identification of driver proteins that underlie disease states, the characterization of regulatory mechanisms controlling the functions of these proteins, their proteoforms, and their interactions, and the progression of transitions from correlation to coexpression to causal networks after system perturbations. And the Human Protein Atlas published Blood, Brain, and Metabolic Atlases.

Bioengineered PBGD variant improves the therapeutic index of gene therapy vectors for acute intermittent porphyria.

A first-in-human gene therapy trial using a recombinant adeno-associated viral (rAAV) vector for acute intermittent porphyria (AIP) reveals that higher doses would be required to reach therapeutic levels of the porphobilinogen deaminase (PBGD) transgene. We developed a hyperfunctional PBGD protein to improve the therapeutic index without increasing vector dose. A consensus protein sequence from 12 mammal species was compared to the human PBGD sequence, and eight amino acids were selected. I291M and N340S variants showed the highest increase in enzymatic activity when expressed in prokaryotic and eukaryotic systems. In silico analysis indicates that isoleucine 291 to methionine and asparagine 340 to serine variants did not affect the active site of the enzyme. In vitro analysis indicated a synergistic interaction between these two substitutions that improve kinetic stability. Finally, full protection against a phenobarbital-induced attack was achieved in AIP mice after the administration of 1 × 1011 gc/kg of rAAV2/8-PBGD-I291M/N340S vector; three times lower than the dose required to achieve full protection with the control rAAV2/8-hPBGD vector. In conclusion, we have developed and characterized a hyperfunctional PBGD protein. The inclusion of this variant sequence in a rAAV2/8 vector allows the effective dose to be lowered in AIP mice.

Progress on Identifying and Characterizing the Human Proteome: 2019 Metrics from the HUPO Human Proteome Project.

The Human Proteome Project (HPP) annually reports on progress made throughout the field in credibly identifying and characterizing the complete human protein parts list and making proteomics an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2019-01-11 contains 17 694 proteins with strong protein-level evidence (PE1), compliant with HPP Guidelines for Interpretation of MS Data v2.1; these represent 89% of all 19 823 neXtProt predicted coding genes (all PE1,2,3,4 proteins), up from 17 470 one year earlier. Conversely, the number of neXtProt PE2,3,4 proteins, termed the "missing proteins" (MPs), has been reduced from 2949 to 2129 since 2016 through efforts throughout the community, including the chromosome-centric HPP. PeptideAtlas is the source of uniformly reanalyzed raw mass spectrometry data for neXtProt; PeptideAtlas added 495 canonical proteins between 2018 and 2019, especially from studies designed to detect hard-to-identify proteins. Meanwhile, the Human Protein Atlas has released version 18.1 with immunohistochemical evidence of expression of 17 000 proteins and survival plots as part of the Pathology Atlas. Many investigators apply multiplexed SRM-targeted proteomics for quantitation of organ-specific popular proteins in studies of various human diseases. The 19 teams of the Biology and Disease-driven B/D-HPP published a total of 160 publications in 2018, bringing proteomics to a broad array of biomedical research.

Human Proteome Project Mass Spectrometry Data Interpretation Guidelines 3.0.

The Human Proteome Organization's (HUPO) Human Proteome Project (HPP) developed Mass Spectrometry (MS) Data Interpretation Guidelines that have been applied since 2016. These guidelines have helped ensure that the emerging draft of the complete human proteome is highly accurate and with low numbers of false-positive protein identifications. Here, we describe an update to these guidelines based on consensus-reaching discussions with the wider HPP community over the past year. The revised 3.0 guidelines address several major and minor identified gaps. We have added guidelines for emerging data independent acquisition (DIA) MS workflows and for use of the new Universal Spectrum Identifier (USI) system being developed by the HUPO Proteomics Standards Initiative (PSI). In addition, we discuss updates to the standard HPP pipeline for collecting MS evidence for all proteins in the HPP, including refinements to minimum evidence. We present a new plan for incorporating MassIVE-KB into the HPP pipeline for the next (HPP 2020) cycle in order to obtain more comprehensive coverage of public MS data sets. The main checklist has been reorganized under headings and subitems, and related guidelines have been grouped. In sum, Version 2.1 of the HPP MS Data Interpretation Guidelines has served well, and this timely update to version 3.0 will aid the HPP as it approaches its goal of collecting and curating MS evidence of translation and expression for all predicted ∼20 000 human proteins encoded by the human genome.

Which Low-Abundance Proteins are Present in the Human Milieu of Gamete/Embryo Maternal Interaction?

The improvement of the embryo culture media is of high relevance due to its influence on successful implantation rates, pregnancy, neonatal outcomes, and potential effects in adult life. The ideal conditions for embryo development are those naturally occurring in the female reproductive tract, i.e., the oviductal and uterine fluids. To shed light on the differences between chemical and natural media, we performed the first comparative study of the low abundance proteins in plasma, uterine, and oviductal fluid collected, simultaneously, from healthy and fertile women that underwent a salpingectomy. The rationale for this design derives from the fact that high-abundant proteins in these fluids are usually those coming from blood serum and frequently mask the detection of low abundant proteins with a potentially significant role in specific processes related to the embryo-maternal interaction. The proteomic analysis by 1D-nano LC ESI-MSMS detected several proteins in higher amounts in oviductal fluid when compared to uterine and plasma samples (RL3, GSTA1, EZRI, DPYSL3, GARS, HSP90A). Such oviductal fluid proteins could be a target to improve fertilization rates and early embryo development if used in the culture media. In conclusion, this study presents a high-throughput analysis of female reproductive tract fluids and contributes to the knowledge of oviductal and uterine secretome.

Identification of the Missing Protein Hyaluronan Synthase 1 in Human Mesenchymal Stem Cells Derived from Adipose Tissue or Umbilical Cord.

Currently, 14% of the human proteome is made up of proteins whose existence is not confirmed by mass spectrometry. We performed a proteomic profiling of human mesenchymal stem cells derived from adipose tissue or umbilical cord (PRIDE accession number: PXD009893) and identified peptides derived from 13 of such missing proteins. Remarkably, we found compelling evidence of the expression of hyaluronan synthase 1 (NX_Q92839-1) and confirmed its identification by the fragmentation of four heavy-labeled peptides that coeluted with their endogenous light counterparts. Our data also suggest that mesenchymal stem cells constitute a promising source for the detection of missing proteins.

Progress on Identifying and Characterizing the Human Proteome: 2018 Metrics from the HUPO Human Proteome Project.

The Human Proteome Project (HPP) annually reports on progress throughout the field in credibly identifying and characterizing the human protein parts list and making proteomics an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2018-01-17, the baseline for this sixth annual HPP special issue of the Journal of Proteome Research, contains 17 470 PE1 proteins, 89% of all neXtProt predicted PE1-4 proteins, up from 17 008 in release 2017-01-23 and 13 975 in release 2012-02-24. Conversely, the number of neXtProt PE2,3,4 missing proteins has been reduced from 2949 to 2579 to 2186 over the past two years. Of the PE1 proteins, 16 092 are based on mass spectrometry results, and 1378 on other kinds of protein studies, notably protein-protein interaction findings. PeptideAtlas has 15 798 canonical proteins, up 625 over the past year, including 269 from SUMOylation studies. The largest reason for missing proteins is low abundance. Meanwhile, the Human Protein Atlas has released its Cell Atlas, Pathology Atlas, and updated Tissue Atlas, and is applying recommendations from the International Working Group on Antibody Validation. Finally, there is progress using the quantitative multiplex organ-specific popular proteins targeted proteomics approach in various disease categories.

Launching the C-HPP neXt-CP50 Pilot Project for Functional Characterization of Identified Proteins with No Known Function.

An important goal of the Human Proteome Organization (HUPO) Chromosome-centric Human Proteome Project (C-HPP) is to correctly define the number of canonical proteins encoded by their cognate open reading frames on each chromosome in the human genome. When identified with high confidence of protein evidence (PE), such proteins are termed PE1 proteins in the online database resource, neXtProt. However, proteins that have not been identified unequivocally at the protein level but that have other evidence suggestive of their existence (PE2-4) are termed missing proteins (MPs). The number of MPs has been reduced from 5511 in 2012 to 2186 in 2018 (neXtProt 2018-01-17 release). Although the annotation of the human proteome has made significant progress, the "parts list" alone does not inform function. Indeed, 1937 proteins representing ∼10% of the human proteome have no function either annotated from experimental characterization or predicted by homology to other proteins. Specifically, these 1937 "dark proteins" of the so-called dark proteome are composed of 1260 functionally uncharacterized but identified PE1 proteins, designated as uPE1, plus 677 MPs from categories PE2-PE4, which also have no known or predicted function and are termed uMPs. At the HUPO-2017 Annual Meeting, the C-HPP officially adopted the uPE1 pilot initiative, with 14 participating international teams later committing to demonstrate the feasibility of the functional characterization of large numbers of dark proteins (CP), starting first with 50 uPE1 proteins, in a stepwise chromosome-centric organizational manner. The second aim of the feasibility phase to characterize protein (CP) functions of 50 uPE1 proteins, termed the neXt-CP50 initiative, is to utilize a variety of approaches and workflows according to individual team expertise, interest, and resources so as to enable the C-HPP to recommend experimentally proven workflows to the proteome community within 3 years. The results from this pilot will not only be the cornerstone of a larger characterization initiative but also enhance understanding of the human proteome and integrated cellular networks for the discovery of new mechanisms of pathology, mechanistically informative biomarkers, and rational drug targets.