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Abstract The Asian green mussel, Perna viridis is an important aquaculture species in the family Mytilidae contributing substantially to molluscan aquaculture. We generated a high-quality chromosome level assembly of this species by combining PacBio single molecule sequencing technique (SMRT), Illumina paired-end sequencing, high-throughput chromosome conformation capture technique (Hi-C) and Bionano mapping. The final assembly resulted in a genome of 723.49 Mb in size with a scaffold N50 of 49.74 Mb with 99% anchored into 15 chromosomes. A total of 49654 protein-coding genes were predicted from the genome. The presence of 634 genes associated with the cancer pathway and 408 genes associated with viral carcinogenesis indicates the potential of this species to be used as a model for cancer studies. The chromosome-level assembly of this species is also a valuable resource for further genomic selection and selective breeding for improving economically important aquaculture traits and augmenting aquaculture productivity.

Abstract The rapid evolution of mass spectrometry-based single-cell proteomics now enables the cataloging of several thousand proteins from single cells. We investigated whether we could discover cellular heterogeneity beyond proteome, encompassing post-translational modifications (PTM), protein-protein interaction, and variants. By optimizing the mass spectrometry data interpretation strategy to enable the detection of PTMs and variants, we have generated a high-definition dataset of single-cell and nuclear proteomic-states. The data demonstrate the heterogeneity of cell-states and signaling dependencies at the single-cell level and reveal epigenetic drug-induced changes in single nuclei. This approach enables the exploration of previously uncharted single-cell and organellar proteomes revealing molecular characteristics that are inaccessible through RNA profiling.

Abstract Background Glycosylation is an enzyme-catalyzed post-translational modification that is distinct from glycation and is present on a majority of plasma proteins. N-glycosylation occurs on asparagine residues predominantly within canonical N-glycosylation motifs (Asn-X-Ser/Thr) although non-canonical N-glycosylation motifs Asn-X-Cys/Val have also been reported. Albumin is the most abundant protein in plasma whose glycation is well-studied in diabetes mellitus. However, albumin has long been considered a non-glycosylated protein due to absence of canonical motifs. Albumin contains two non-canonical N-glycosylation motifs, of which one was recently reported to be glycosylated. Methods We enriched abundant serum proteins to investigate their N-linked glycosylation followed by trypsin digestion and glycopeptide enrichment by size-exclusion or mixed-mode anion-exchange chromatography. Glycosylation at canonical as well as non-canonical sites was evaluated by liquid chromatography–tandem mass spectrometry (LC–MS/MS) of enriched glycopeptides. Deglycosylation analysis was performed to confirm N-linked glycosylation at non-canonical sites. Albumin-derived glycopeptides were fragmented by MS3 to confirm attached glycans. Parallel reaction monitoring was carried out on twenty additional samples to validate these findings. Bovine and rabbit albumin-derived glycopeptides were similarly analyzed by LC–MS/MS. Results Human albumin is N-glycosylated at two non-canonical sites, Asn68 and Asn123. N-glycopeptides were detected at both sites bearing four complex sialylated glycans and validated by MS3-based fragmentation and deglycosylation studies. Targeted mass spectrometry confirmed glycosylation in twenty additional donor samples. Finally, the highly conserved Asn123 in bovine and rabbit serum albumin was also found to be glycosylated. Conclusions Albumin is a glycoprotein with conserved N-linked glycosylation sites that could have potential clinical applications.

BackgroundMultiple sclerosis (MS) is a demyelinating disease of the central nervous system characterized by increased inflammation and immune responses, oxidative injury, mitochondrial dysfunction, and iron dyshomeostasis leading to demyelination and axonal damage. In MS, incomplete remyelination results in chronically demyelinated axons and degeneration coinciding with disability. This suggests a failure in the ability to remyelinate in MS, however, the precise underlying mechanisms remain unclear. We aimed to identify proteins whose expression was altered in chronic inactive white matter lesions and periplaque white matter in MS tissue to reveal potential pathophysiological mechanisms.MethodsLaser capture microdissection coupled to proteomics was used to interrogate spatially altered changes in formalin-fixed paraffin-embedded brain tissue from three chronic MS individuals and three controls with no apparent neurological complications. Histopathological maps guided the capture of inactive lesions, periplaque white matter, and cortex from chronic MS individuals along with corresponding white matter and cortex from control tissue. Label free quantitation by liquid chromatography tandem mass spectrometry was used to discover differentially expressed proteins between the various brain regions.ResultsIn addition to confirming loss of several myelin-associated proteins known to be affected in MS, proteomics analysis of chronic inactive MS lesions revealed alterations in myelin assembly, metabolism, and cytoskeletal organization. The top altered proteins in MS inactive lesions compared to control white matter consisted of PPP1R14A, ERMN, SIRT2, CARNS1, and MBLAC2.ConclusionOur findings highlight proteome changes in chronic inactive MS white matter lesions and periplaque white matter, which may be crucial for proper myelinogenesis, bioenergetics, focal adhesions, and cellular function. This study highlights the importance and feasibility of spatial approaches such as laser capture microdissection-based proteomics analysis of pathologically distinct regions of MS brain tissue. Identification of spatially resolved changes in the proteome of MS brain tissue should aid in the understanding of pathophysiological mechanisms and the development of novel therapies.

Background & Aims: Metabolomic and lipidomic analyses provide an opportunity for novel biological insights. Cholangiocarcinoma (CCA) remains a highly lethal cancer with limited response to systemic, targeted, and immunotherapeutic approaches. Using a global metabolomics and lipidomics platform, this study aimed to discover and characterize metabolomic variations and associated pathway derangements in patients with CCA. Methods: Leveraging a biospecimen collection, including samples from patients with digestive diseases and normal controls, global serum metabolomic and lipidomic profiling was performed on 213 patients with CCA and 98 healthy controls. The CCA cohort of patients included representation of intrahepatic, perihilar, and distal CCA tumours. Metabolome-wide association studies utilizing multivariable linear regression were used to perform case–control comparisons, followed by pathway enrichment analysis, CCA subtype analysis, and disease stage analysis. The impact of biliary obstruction was evaluated by repeating analyses in subsets of patients only with normal bilirubin levels. Results: Of the 420 metabolites that discriminated patients with CCA from controls, decreased abundance of cysteine-glutathione disulfide was most closely associated with CCA. Additional conjugated bile acid species were found in increased abundance even in the absence of clinically relevant biliary obstruction denoted by elevated serum bilirubin levels. Pathway enrichment analysis also revealed alterations in caffeine metabolism and mitochondrial redox-associated pathways in the serum of patients with CCA. Conclusions: The presented metabolomic and lipidomic profiling demonstrated multiple alterations in the serum of patients with CCA. These exploratory data highlight novel metabolic pathways in CCA and support future work in therapeutic targeting of these pathways and the development of a precision biomarker panel for diagnosis. Impact and implications: Cholangiocarcinoma (CCA) is a highly lethal hepatobiliary cancer with limited treatment response, highlighting the need for a better understanding of the disease biology. Using a global metabolomics and lipidomics platform, we characterized distinct changes in the serum of 213 patients with CCA compared with healthy controls. The results of this study elucidate novel metabolic pathways in CCA. These findings benefit stakeholders in both the clinical and research realms by providing a foundation for improved disease diagnostics and identifying novel targets for therapeutic design.

Microorganisms, crucial for environmental equilibrium, could be destructive, resulting in detrimental pathophysiology to the human host. Moreover, with the emergence of antibiotic resistance (ABR), the microbial communities pose the century’s largest public health challenges in terms of effective treatment strategies. Furthermore, given the large diversity and number of known bacterial strains, describing treatment choices for infected patients using experimental methodologies is time-consuming. An alternative technique, gaining popularity as sequencing prices fall and technology advances, is to use bacterial genotype rather than phenotype to determine ABR. Complementing machine learning into clinical practice provides a data-driven platform for categorization and interpretation of bacterial datasets. In the present study, k-mers were generated from nucleotide sequences of pathogenic bacteria resistant to antibiotics. Subsequently, they were clustered into groups of bacteria sharing similar genomic features using the Affinity propagation algorithm with a Silhouette coefficient of 0.82. Thereafter, a prediction model based on Random Forest algorithm was developed to explore the prediction capability of the k-mers. It yielded an overall specificity of 0.99 and a sensitivity of 0.98. Additionally, the genes and ABR drivers related to the k-mers were identified to explore their biological relevance. Furthermore, a multilayer perceptron model with a hamming loss of 0.05 was built to classify the bacterial strains into resistant and non-resistant strains against various antibiotics. Segregating pathogenic bacteria based on genomic similarities could be a valuable approach for assessing the severity of diseases caused by new bacterial strains. Utilization of this strategy could aid in enhancing our understanding of ABR patterns, paving the way for more informed and effective treatment options.

Abstract Endoxifen, a secondary tamoxifen metabolite, is a potent antiestrogen exhibiting estrogen receptor alpha (ERα) binding at nanomolar concentrations. Phase I/II clinical trials identified clinical activity of Z-endoxifen (ENDX), in endocrine-refractory metastatic breast cancer as well as ERα+ solid tumors, raising the possibility that ENDX may have a second, ERα-independent, mechanism of action. An unbiased mass spectrometry approach revealed that ENDX concentrations achieved clinically with direct ENDX administration (5 µM), but not low concentrations observed during tamoxifen treatment (

Summary: Phosphomannomutase 2-congenital disorder of glycosylation (PMM2-CDG) is a rare inborn error of metabolism caused by deficiency of the PMM2 enzyme, which leads to impaired protein glycosylation. While the disorder presents with primarily neurological symptoms, there is limited knowledge about the specific brain-related changes caused by PMM2 deficiency. Here, we demonstrate aberrant neural activity in 2D neuronal networks from PMM2-CDG individuals. Utilizing multi-omics datasets from 3D human cortical organoids (hCOs) derived from PMM2-CDG individuals, we identify widespread decreases in protein glycosylation, highlighting impaired glycosylation as a key pathological feature of PMM2-CDG, as well as impaired mitochondrial structure and abnormal glucose metabolism in PMM2-deficient hCOs, indicating disturbances in energy metabolism. Correlation between PMM2 enzymatic activity in hCOs and symptom severity suggests that the level of PMM2 enzyme function directly influences neurological manifestations. These findings enhance our understanding of specific brain-related perturbations associated with PMM2-CDG, offering insights into the underlying mechanisms and potential directions for therapeutic interventions.

BackgroundHofbauer cells (HBCs) and cytotrophoblasts (CTBs) are major cell populations in placenta. The indirect impact of maternal SARS-CoV-2 disease on these cells that are not directly infected has not been extensively studied. Herein, we profiled gene expression in HBCs and CTBs isolated from placentae of recovered pregnant subjects infected with SARS-CoV-2 during all trimesters of pregnancy, placentae from subjects with active infection, SARS-CoV-2 vaccinated subjects, and those who were unexposed to the virus.MethodsPlacentae were collected within 4 h post-delivery and membrane-free tissues were enzymatically digested for the isolation of HBCs and CTBs. RNA extracted from HBCs and CTBs were sequenced using 150bp paired-end reads. Differentially expressed genes (DEGs) were identified by DESeq2 package in R and enriched in GO Biological Processes, KEGG Pathway, Reactome Gene Sets, Hallmark Gene Sets, and Canonical Pathways. Protein-protein interactions among the DEGs were modelled using STRING and BioGrid.ResultsPregnant subjects (n = 30) were recruited and categorized into six groups: infected with SARS-CoV-2 in i) the first (1T, n = 4), ii) second (2T, n = 5), iii) third (3T, n = 5) trimester, iv) tested positive at delivery (Delivery, n = 5), v) never infected (Control, n = 6), and vi) fully mRNA-vaccinated by delivery (Vaccinated, n = 5). Compared to the Control group, gene expression analysis showed that HBCs from infected subjects had significantly altered gene expression profiles, with the 2T group having the highest number of DEGs (1,696), followed by 3T and 1T groups (1,656 and 958 DEGs, respectively). These DEGs were enriched for pathways involved in immune regulation for host defense, including production of cytokines, chemokines, antimicrobial proteins, ribosomal assembly, neutrophil degranulation inflammation, morphogenesis, and cell migration/adhesion. Protein-protein interaction analysis mapped these DEGs with oxidative phosphorylation, translation, extracellular matrix organization, and type I interferon signaling. Only 95, 23, and 8 DEGs were identified in CTBs of 1T, 2T, and 3T groups, respectively. Similarly, 11 and 3 DEGs were identified in CTBs and HBCs of vaccinated subjects, respectively. Reassuringly, mRNA vaccination did not induce an inflammatory response in placental cells.ConclusionsOur studies demonstrate a significant impact of indirect SARS-CoV-2 infection on gene expression of inner mesenchymal HBCs, with limited effect on lining CTB cells isolated from pregnant subjects infected and recovered from SARS-CoV-2. The pathways associated with these DEGs identify potential targets for therapeutic intervention.

Objective: We sought to identify differentially expressed proteins in serum, plasma, and plaque samples of patients with carotid atherosclerotic lesions. Methods: We performed a systematic review of the proteomic profile of serum, plasma, and plaque samples of patients with carotid artery disease. We included full-length peer-reviewed studies of adult humans and reported them using PRISMA guidelines. The quality of the design and content of the articles included in the review was assessed using the Newcastle-Ottawa scale. Results: We included six peer-reviewed articles reporting protein expression in serum, plasma, or plaque samples from patients with carotid atherosclerosis. Three were single-center cross-sectional studies, two were single-center case-control studies, and one was a single-center cohort study. Thirty-six proteins were found to be expressed differentially when comparing samples from healthy subjects and individuals with diseased carotid vessels and between patients with symptomatic and asymptomatic carotid artery atherosclerotic lesions. Some of these were shown to be related to inflammatory or anti-inflammatory pathways in atherogenesis. CD5L and S100A12 were both found to be upregulated in patients with unstable plaque, the former owing to its anti-inflammatory properties and the latter for its pro-oxidant effects in atherosclerosis. ACTB is involved in cellular structure and integrity and was found to be downregulated in patients with ruptured carotid plaques. Conclusions: Atherosclerotic carotid disease places the patient at increased risk of ischemic neurological events. Proteomics may help to understand their pathophysiological processes and can identify differential protein expression in blood samples from healthy subjects and patients with carotid artery plaques. This patient-centered approach will allow for the timely identification of individuals at higher risk of experiencing stroke.

Abstract Background The rare p.H157Y variant of TREM2 (Triggering Receptor Expressed on Myeloid Cells 2) was found to increase Alzheimer’s disease (AD) risk. This mutation is located at the cleavage site of TREM2 extracellular domain. Ectopic expression of TREM2-H157Y in HEK293 cells resulted in increased TREM2 shedding. However, the physiological outcomes of the TREM2 H157Y mutation remain unknown in the absence and presence of AD related pathologies. Methods We generated a novel Trem2 H157Y knock-in mouse model through CRISPR/Cas9 technology and investigated the effects of Trem2 H157Y on TREM2 proteolytic processing, synaptic function, and AD-related amyloid pathologies by conducting biochemical assays, targeted mass spectrometry analysis of TREM2, hippocampal electrophysiology, immunofluorescent staining, in vivo micro-dialysis, and cortical bulk RNA sequencing. Results Consistent with previous in vitro findings, Trem2 H157Y increases TREM2 shedding with elevated soluble TREM2 levels in the brain and serum. Moreover, Trem2 H157Y enhances synaptic plasticity without affecting microglial density and morphology, or TREM2 signaling. In the presence of amyloid pathology, Trem2 H157Y accelerates amyloid-β (Aβ) clearance and reduces amyloid burden, dystrophic neurites, and gliosis in two independent founder lines. Targeted mass spectrometry analysis of TREM2 revealed higher ratios of soluble to full-length TREM2-H157Y compared to wild-type TREM2, indicating that the H157Y mutation promotes TREM2 shedding in the presence of Aβ. TREM2 signaling was further found reduced in Trem2 H157Y homozygous mice. Transcriptomic profiling revealed that Trem2 H157Y downregulates neuroinflammation-related genes and an immune module correlated with the amyloid pathology. Conclusion Taken together, our findings suggest beneficial effects of the Trem2 H157Y mutation in synaptic function and in mitigating amyloid pathology. Considering the genetic association of TREM2 p.H157Y with AD risk, we speculate TREM2 H157Y in humans might increase AD risk through an amyloid-independent pathway, such as its effects on tauopathy and neurodegeneration which merit further investigation.

Abstract Acquired sporadic late onset nemaline myopathy (SLONM) and inherited nemaline myopathy (iNM) both feature accumulation of nemaline rods in muscle fibers. Unlike iNM, SLONM is amenable to therapy. The distinction between these disorders is therefore crucial when the diagnosis remains ambiguous after initial investigations. We sought to identify biomarkers facilitating this distinction and to investigate the pathophysiology of nemaline rod formation in these different disorders. Twenty-two muscle samples from patients affected by SLONM or iNM underwent quantitative histological analysis, laser capture microdissection for proteomic analysis of nemaline rod areas and rod-free areas, and transcriptomic analysis. In all iNM samples, nemaline rods were found in subsarcolemmal or central aggregates, whereas they were diffusely distributed within muscle fibers in most SLONM samples. In SLONM, muscle fibers harboring nemaline rods were smaller than those without rods. Necrotic fibers, increased endomysial connective tissue, and atrophic fibers filled with nemaline rods were more common in SLONM. Proteomic analysis detected differentially expressed proteins between nemaline rod areas and rod-free areas, as well as between SLONM and iNM. These differentially expressed proteins implicated immune, structural, metabolic, and cellular processes in disease pathophysiology. Notably, immunoglobulin overexpression with accumulation in nemaline rod areas was detected in SLONM. Transcriptomic analysis corroborated proteomic findings and further revealed substantial gene expression differences between SLONM and iNM. Overall, we identified unique pathological and molecular signatures associated with SLONM and iNM, suggesting distinct underlying pathophysiological mechanisms. These findings represent a step towards enhanced diagnostic tools and towards development of treatments for SLONM.

Epitaxial GaN nanostructures are developed, and the influence of the AlN buffer layer (temperature modulation) on material characteristics and optoelectronic device application is assessed. The AlN buffer layer was grown on a Si (111) substrate at varying temperatures (770–830 °C), followed by GaN growth using plasma-assisted molecular beam epitaxy. The investigation revealed that the comparatively lower temperature AlN buffer layer was responsible for stress and lattice strain relaxation and was realized as the GaN nano-obelisk structures. Contrarily, the increased temperature of the AlN growth led to the formation of GaN nanopyramidal and nanowax/wane structures. These grown GaN/AlN/Si heterostructures were utilized to develop photodetectors in a metal–semiconductor–metal geometry format. The performance of these fabricated optoelectronic devices was examined under ultraviolet illumination (UVA), where the GaN nano-obelisks-based device attained the highest responsivity of 118 AW−1. Under UVA (325 nm) illumination, the designed device exhibited a high detectivity of 1 × 1010 Jones, noise equivalent power of 1 × 10−12 WHz−1/2, and external quantum efficiency of 45,000%. The analysis revealed that the quality of the AlN buffer layer significantly improved the optoelectronic performance of the device.

Abstract Non-functioning pituitary tumours (NF-PitNETs) are common intracranial benign neoplasms that can exhibit aggressive behaviour by invading neighbouring structures and, in some cases, have multiple recurrences. Despite resulting in severe co-morbidities, no predictive biomarkers of recurrence have been identified for NF-PitNETs. In this study we have used high-throughput mass spectrometry-based analysis to examine the phosphorylation pattern of different subsets of NF-PitNETs. Based on histopathological, radiological, surgical and clinical features, we have grouped NF-PitNETs into non-invasive, invasive, and recurrent disease groups. Tumour recurrence was determined based on regular clinical and radiological data of patients for a mean follow-up of 10 years (SD ± 5.4 years). Phosphoproteomic analyses identified a unique phosphopeptide enrichment pattern which correlates with disease recurrence. Candidate phosphorylated proteins were validated in a large cohort of NF-PitNET patients by western blot and immunohistochemistry. We identified a cluster of 22 phosphopeptides upregulated in recurrent NF-PitNETs compared to non-invasive and invasive subgroups. We reveal significant phosphorylation of the β-catenin at Ser552 in recurrent and invasive NF-PitNETs, compared to non-invasive/non-recurrent NF-PitNET subgroup. Moreover, β-catenin pSer552 correlates with the recurrence free survival among 200 patients with NF-PitNET. Together, our results suggest that the phosphorylation status of β-catenin at Ser552 could act as potential biomarker of tumour recurrence in NF-PitNETs.

Esophageal squamous cell carcinoma (ESCC) is the most prevalent malignant gastrointestinal tumor. Ion channels contribute to tumor growth and progression through interactions with their neighboring molecules including lipids. The dysregulation of membrane ion channels and lipid metabolism may contribute to the epithelial–mesenchymal transition (EMT), leading to metastatic progression. Herein, transcriptome profiles of patients with ESCC were analyzed by performing differential gene expression and weighted gene co-expression network analysis to identify the altered ion channels, lipid metabolism- and EMT-related genes in ESCC. A total of 1,081 differentially expressed genes, including 113 ion channels, 487 lipid metabolism-related, and 537 EMT-related genes, were identified in patients with ESCC. Thereafter, EMT scores were correlated with altered co-expressed genes. The altered co-expressed genes indicated a correlation with EMT signatures. Interactions among 22 ion channels with 3 hub lipid metabolism- and 13 hub EMT-related proteins were determined using protein–protein interaction networks. A pathway map was generated to depict deregulated signaling pathways including insulin resistance and the estrogen receptor-Ca2+ signaling pathway in ESCC. The relationship between potential ion channels and 5-year survival rates in ESCC was determined using Kaplan–Meier plots and Cox proportional hazard regression analysis. Inositol 1,4,5-trisphosphate receptor type 3 (ITPR3) was found to be associated with poor prognosis of patients with ESCC. Additionally, drugs interacting with potential ion channels, including GJA1 and ITPR3, were identified. Understanding alterations in ion channels with lipid metabolism and EMT in ESCC pathophysiology would most likely provide potential targets for the better treatment of patients with ESCC.

Abstract Epithelial–mesenchymal transition (EMT) is a dynamic and complex cellular process that is known to be hijacked by cancer cells to facilitate invasion, metastasis and therapeutic resistance. Several quantitative measures to assess the interplay between EMT and cancer progression are available, based on large scale genome and transcriptome data. However, these large scale multi-omics studies have repeatedly illustrated a lack of correlation in mRNA and protein abundances that may be influenced by diverse post-translational regulation. Hence, it is imperative to understand how changes in the EMT proteome are associated with the process of oncogenic transformation. To this effect, we developed a parallel reaction monitoring-based targeted proteomics method for quantifying abundances of EMT-associated proteins across cancer cell lines. Our study revealed that quantitative measurement of EMT proteome which enabled a more accurate assessment than transcriptomics data and revealed specific discrepancies against a backdrop of generally strong concordance between proteomic and transcriptomic data. We further demonstrated that changes in our EMT proteome panel might play a role in tumor transformation across cancer types. In future, this EMT panel assay has the potential to be used for clinical samples to guide treatment choices and to congregate functional information for the development and advancing novel therapeutics.

Infantile neuroaxonal dystrophy (INAD) is caused by recessive variants in PLA2G6 and is a lethal pediatric neurodegenerative disorder. Loss of the Drosophila homolog of PLA2G6, leads to ceramide accumulation, lysosome expansion, and mitochondrial defects. Here, we report that retromer function, ceramide metabolism, the endolysosomal pathway, and mitochondrial morphology are affected in INAD patient-derived neurons. We show that in INAD mouse models, the same features are affected in Purkinje cells, arguing that the neuropathological mechanisms are evolutionary conserved and that these features can be used as biomarkers. We tested 20 drugs that target these pathways and found that Ambroxol, Desipramine, Azoramide, and Genistein alleviate neurodegenerative phenotypes in INAD flies and INAD patient-derived neural progenitor cells. We also develop an AAV-based gene therapy approach that delays neurodegeneration and prolongs lifespan in an INAD mouse model.

Lipidomics is an important component of most multi-Omics systems biology studies and is largely driven by mass spectrometry (MS). Because lipids are tight regulators of multiple cellular functions, including energy homeostasis, membrane structures and cell signaling, lipidomics can provide a deeper understanding of variations underlying disease states and can become an even more powerful platform when combined with other omics, including genomics or proteomics. However, data analysis, especially in lipid annotation, poses challenges due to the heterogeneity of functional head groups and fatty acyl chains of varying hydrocarbon lengths and degrees of unsaturation. As there are various MS/MS fragmentation sites in lipids that are class-dependent, obtaining MS/MS data that includes as many fragment ions as possible is critical for structural characterization of lipids in lipidomics workflow. Here, we report an improved lipidomics methodology that resulted in increased coverage of lipidome using: 1) An automated data-driven MS/MS acquisition scheme in which inclusion and exclusion lists were automatically generated from the full scan MS of sample injections, followed by creation of updated lists over iterative analyses; and, 2) Incorporation of dual dissociation techniques of higher-energy collision dissociation and collision-induced dissociation for more accurate characterization of phosphatidylcholine species. Inclusion lists were created automatically based on full scan MS signals from samples and through iterative analyses, ions in the inclusion list that were fragmented were automatically moved to the exclusion list in subsequent runs. We confirmed that analytes with low MS response that did not undergo MS/MS events in conventional data-dependent analysis were successfully fragmented using this approach. Overall, this automated data-driven data acquisition approach resulted in a higher coverage of lipidome and the use of dual dissociation techniques provided additional information that was critical in characterizing the side chains of phosphatidylcholine species.

Tongue squamous cell carcinoma is an aggressive oral cancer with a high incidence of metastasis and poor prognosis. Most of the oral cavity cancer patients present in clinics with locally advanced unresectable tumors. Neoadjuvant treatment is beneficial for these individuals as it reduces the tumor size aiding complete resection. However, patients develop therapy resistance to the drug regimen. In this study, we explored the differential expression of proteins and altered phosphorylation in the neoadjuvant chemotherapy resistant tongue cancer patients. We integrated the proteomic and phosphoproteomic profiles of resistant (n = 4) and sensitive cohorts (n = 4) and demonstrated the differential expression and phosphorylation of proteins in the primary tissue of the respective subject groups. We observed differential and extensive phosphorylation of keratins such as KRT10 and KRT1 between the two cohorts. Furthermore, our study revealed a kinase signature associated with neoadjuvant chemotherapy resistance. Kinases such as MAPK1, AKT1, and MAPK3 are predicted to regulate the resistance in non-responders. Pathway analysis showed enrichment of Rho GTPase signaling and hyperphosphosphorylation of proteins involved in cell motility, invasion, and drug resistance. Targeting the kinases could help with the clinical management of neoadjuvant chemotherapy-resistant tongue cancer.

Purpose: Age-related macular degeneration (AMD) is one of the leading causes of irreversible central vision loss in the elderly population. The current study aims to find non-invasive prognostic biomarkers in the urine specimens of the AMD patients. Methods: Peripheral blood and urine samples were collected from 23 controls and 61 AMD patients. Genomic DNA was extracted from the buffy coat of peripheral blood. Allele specific PCR was used to assay SNPs in complement factor H (CFH), complement component 3 (C3). Comparative proteomic analysis of urine samples from early AMD, choroidal neovascular membrane (CNVM), geographic atrophy (GA), and healthy controls was performed using isobaric labelling followed by mass spectrometry. Validation was performed using enzyme-linked immunosorbent assay (ELISA). Results: Comparative proteomic analysis of urine samples identified 751 proteins, of which 383 proteins were found to be differentially expressed in various groups of AMD patients. Gene ontology classification of differentially expressed proteins revealed the majority of them were involved in catalytic functions and binding activities. Pathway analysis showed cell adhesion molecule pathways (CAMs), Complement and coagulation cascades, to be significantly deregulated in AMD. Upon validation by ELISA, SERPINA-1 (Alpha1 antitrypsin), TIMP-1 (Tissue inhibitor of matrix metaloprotease-1), APOA-1 (Apolipoprotein A-1) were significantly over-expressed in AMD (n = 61) patients compared to controls (n = 23). A logistic model of APOA-1 in combination with CFH and C3 polymorphisms predicted the risk of developing AMD with 82% accuracy. Conclusion: This study gives us a preliminary data on non-invasive predictive biomarkers for AMD, which can be further validated in a large cohort and translated for diagnostic use.

The present study was planned to characterize the morphological features of local buffalo populations found in the Mahakaushal region of Madhya Pradesh as per the guideline of ICAR-NBAGR, Karnal. The study revealed that the buffalo population was generally distributed in Jabalpur, Mandla, Dindori, Seoni and adjoining parts of the districts. The study revealed that the size of buffalo in Mahakaushal region was medium to large with compact body and had a black, light brown or grey body coat and skin colour. The most common colour of muzzle was black, light black eyelids and hooves, light grey horns and light black tail-switch. There were few buffaloes which had white marking on forehead and tail switch. This study was the first attempt to examine the buffalo population in this region. The present study reveals that the studied buffalo population can be registered as a breed.

ABSTRACT: The COVID-19 pandemic has necessitated exploration of alternative testing methods for detection of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) to ensure clinical laboratories can continue to provide critical testing results. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is established in many clinical laboratories due its high specificity and sensitivity, making it a logical alternative methodology. However, matching the sensitivity of quantitative reverse transcription-polymerase chain reaction (qRT-PCR) remains challenging, which forced utilization of antibody-based enrichment prior to targeted LC-MS/MS analysis. When utilizing antibody purification techniques, investigators must decide whether to enrich the target protein or peptides, but there are few studies comparing the two approaches to assist in this decision-making process. In this work, we present a comparison of intact protein and peptide antibody-based purification for LC-MS/MS based detection of SARS-CoV-2. We have found that protein purification yields more intense LC-MS/MS signals, but is also less specific, yielding higher noise and more background when compared to peptide purification techniques. Therefore, when using traditional data analysis techniques, the enrichment technique that provides superior sensitivity varies for individual peptides and no definitive overall conclusion can be made. These observations are corroborated when using a novel machine learning approach to determine positive/negative test results, which yielded superior sensitivity when using protein purification, but better specificity and area under the ROC curve when performing peptide purification.

Gallbladder cancer incidence shows characteristic geographic patterns. Here the authors perform a genomic analysis of gallbladder cancers in patients from countries with high incidence (South Korea, India and Chile) and identify ELF3 and other significantly mutated genes not previously associated with gallbladder cancer.

Through lateral transfer, extra-cellular vesicles (EVs) transport their DNA, miRNA, mRNA and proteins such as enzymes mediating drug resistance, transporters as well as growth factors to neighboring cells. By virtue of this horizontal transfer, EVs potentially regulate cell growth, migration, angiogenesis and metastasis and increase tissue permeability in cancer. Furthermore, EVs regulate immune factors and allow the tumor cells to evade immune recognition and cell death. To explore if the proteomes of exosomes support functional transfer of cancer hallmarks, in this meta-analysis, we compared EVs and whole cell proteomes from the NCI-60 human tumor cell line panel. We observed a subgroup of proteins in each cancer hallmark signature as highly abundant and consistently expressed in EVs from all cell lines. Among these were oncoproteins frequently targeted in cancer therapies whose presence on EVs could potentially render therapies less effective by serving as decoys.

Epithelial-mesenchymal transition (EMT) is a dynamic process by which the cells transdifferentiate into two or more somatic states. The metastatic spread begins with tumor cells disseminated from the primary tumor via intravasation, hematogenous transit and extravasation to reach the distant organs to form micro- or macrometastasis. Dissemination of tumor cells or metastasis is a crucial stage in cancer progression and accounts for majority of cancer associated morbidity and mortality. Advances in technology has now enabled detection and capture of tumor cells that escape from primary site into the bloodstream. Such tumor cells which are found in transit in the blood are referred to as circulating tumor cells (CTCs) and they represent the early step in metastatic cascade. The dynamic changes in EMT phenotype in CTCs plays a key role in cancer metastasis. This review will focus on the role of EMT in cancer progression, circulating tumor cells and its clinical relevance.

Introduction: Emphysematous pyelonephritis (EPN), an acute necrotizing infection of the kidney and surrounding tissues, is associated with considerable mortality. We evaluated how existing critical care scoring systems could predict the need for intensive care unit (ICU) management for these patients. We also analyzed if CT-imaging further enhances these predictive systems. Patients and Methods: A retrospective analysis of 90 consecutive patients diagnosed clinico-radiologically with EPN from January 2011 to September 2020. Five scoring systems were evaluated for their predictive ability for the need for ICU management and mortality risk: National Early Warning Score (NEWS), Modified Early Warning Score (MEWS), ‘quick’ Sequential Organ Failure Assessment score (qSOFA), Systemic Inflammatory Response Syndrome score (SIRS), and Sequential Organ Failure Assessment score (SOFA). CT images were classified as per Huang & Tseng and evaluated as stand-alone or added to the different predictive models. Receiver operating characteristic (ROC) curves were plotted for each critical care score and CT-Class using logistic regression, to obtain the area under curve (AUC) value for comparison of ICU admission predictability. Patients were analyzed up till discharge. Results: Ninety patients were diagnosed with EPN. Twenty-six patients required ICU management and nine patients died. The best scoring system to predict the need of early ICU management is NEWS (AUC 0.884). CT Class had no independent predictive power, nor did it add significantly to improvement in most of the early warning scoring systems, but rather guided us to the need for radiological, endourological or surgical intervention. Conclusion: In patients with EPN, the NEWS scoring system predicts best the requirement of ICU care. It aids in triage of patients with EPN to appropriate early management and reduce mortality risk.

Protein arginine methylation is an extensive and functionally significant post-translational modification. However, little is known about its role in differentiation at the systems level. Using stable isotope labeling by amino acids in cell culture (SILAC) proteomics of whole proteome analysis in proliferating or five-day differentiated mouse C2C12 myoblasts, followed by high-resolution mass spectrometry, biochemical assays, and specific immunoprecipitation of mono- or dimethylated arginine peptides, we identified several protein families that were differentially methylated on arginine. Our study is the first to reveal global changes in the arginine mono- or dimethylation of proteins in proliferating myoblasts and differentiated myocytes and to identify enriched protein domains and novel short linear motifs (SLiMs). Our data may be crucial for dissecting the links between differentiation and cancer growth.

Extracellular vesicles (EVs) are emerging mediators of intercellular communication in nonalcoholic steatohepatitis (NASH). Palmitate, a lipotoxic saturated fatty acid, activates hepatocellular endoplasmic reticulum stress, which has been demonstrated to be important in NASH pathogenesis, including in the release of EVs. We have previously demonstrated that the release of palmitate-stimulated EVs is dependent on the de novo synthesis of ceramide, which is trafficked by the ceramide transport protein, STARD11. The trafficking of ceramide is a critical step in the release of lipotoxic EVs, as cells deficient in STARD11 do not release palmitate-stimulated EVs. Here, we examined the hypothesis that protein cargoes are trafficked to lipotoxic EVs in a ceramide-dependent manner. We performed quantitative proteomic analysis of palmitate-stimulated EVs in control and STARD11 knockout hepatocyte cell lines. Proteomics was performed on EVs isolated by size exclusion chromatography, ultracentrifugation, and density gradient separation, and EV proteins were measured by mass spectrometry. We also performed human EV proteomics from a control and a NASH plasma sample, for comparative analyses with hepatocyte-derived lipotoxic EVs. Size exclusion chromatography yielded most unique EV proteins. Ceramide-dependent lipotoxic EVs contain damage-associated molecular patterns and adhesion molecules. Haptoglobin, vascular non-inflammatory molecule-1, and insulin-like growth factor-binding protein complex acid labile subunit were commonly detected in NASH and hepatocyte-derived ceramide-dependent EVs. Lipotoxic EV proteomics provides novel candidate proteins to investigate in NASH pathogenesis and as diagnostic biomarkers for hepatocyte-derived EVs in NASH patients.

Background: The COVID-19 pandemic caused by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) has overwhelmed health systems worldwide and highlighted limitations of diagnostic testing. Several types of diagnostic tests including RT-PCR-based assays and antigen detection by lateral flow assays, each with their own strengths and weaknesses, have been developed and deployed in a short time. Methods: Here, we describe an immunoaffinity purification approach followed a by high resolution mass spectrometry-based targeted qualitative assay capable of detecting SARS-CoV-2 viral antigen from nasopharyngeal swab samples. Based on our discovery experiments using purified virus, recombinant viral protein and nasopharyngeal swab samples from COVID-19 positive patients, nucleocapsid protein was selected as a target antigen. We then developed an automated antibody capture-based workflow coupled to targeted high-field asymmetric waveform ion mobility spectrometry (FAIMS) - parallel reaction monitoring (PRM) assay on an Orbitrap Exploris 480 mass spectrometer. An ensemble machine learning-based model for determining COVID-19 positive samples was developed using fragment ion intensities from the PRM data. Findings: The optimized targeted assay, which was used to analyze 88 positive and 88 negative nasopharyngeal swab samples for validation, resulted in 98% (95% CI = 0.922–0.997) (86/88) sensitivity and 100% (95% CI = 0.958–1.000) (88/88) specificity using RT-PCR-based molecular testing as the reference method. Interpretation: Our results demonstrate that direct detection of infectious agents from clinical samples by tandem mass spectrometry-based assays have potential to be deployed as diagnostic assays in clinical laboratories, which has hitherto been limited to analysis of pure microbial cultures.

Breast cancer is the most common malignancy among women, with the highest incidence rate worldwide. Dysregulation of long noncoding RNAs during the preliminary stages of breast carcinogenesis is poorly understood. In this study, we performed RNA sequencing to identify long noncoding RNA expression profiles associated with early‐stage breast cancer. RNA sequencing was performed on six invasive ductal carcinoma (IDC) tissues along with paired normal tissue samples, seven ductal carcinoma in situ tissues, and five apparently normal breast tissues. We identified 375 differentially expressed lncRNAs (DElncRNAs) in IDC tissues compared to paired normal tissues. Antisense transcripts (~ 58%) were the largest subtype among DElncRNAs. About 20% of the 375 DElncRNAs were supported by typical split readings leveraging their detection confidence. Validation was performed in n = 52 IDC and paired normal tissue by qRT‐PCR for the identified targets (ADAMTS9‐AS2, EPB41L4A‐AS1, WDFY3‐AS2, RP11‐295M3.4, RP11‐161M6.2, RP11‐490M8.1, CTB‐92J24.3, and FAM83H‐AS1). We evaluated the prognostic significance of DElncRNAs based on TCGA datasets and report that overexpression of FAM83H‐AS1 was associated with patient poor survival. We confirmed that the downregulation of ADAMTS9‐AS2 in breast cancer was due to promoter hypermethylation through in vitro silencing experiments and pyrosequencing.

The parasitic mite Sarcoptes scabiei is an economically highly significant parasite of the skin of humans and animals worldwide. In humans, this mite causes a neglected tropical disease (NTD), called scabies. This disease results in major morbidity, disability, stigma and poverty globally and is often associated with secondary bacterial infections. Currently, anti-scabies treatments are not sufficiently effective, resistance to them is emerging and no vaccine is available. Here, we report the first high-quality genome and transcriptomic data for S. scabiei. The genome is 56.6 Mb in size, has a a repeat content of 10.6% and codes for 9,174 proteins. We explored key molecules involved in development, reproduction, host-parasite interactions, immunity and disease. The enhanced 'omic data sets for S. scabiei represent comprehensive and critical resources for genetic, functional genomic, metabolomic, phylogenetic, ecological and/or epidemiological investigations, and will underpin the design and development of new treatments, vaccines and/or diagnostic tests.

Summary: Many gene products exhibit great structural heterogeneity because of an array of modifications. These modifications are not directly encoded in the genomic template but often affect the functionality of proteins. Protein glycosylation plays a vital role in proper protein functions. However, the analysis of glycoproteins has been challenging compared with other protein modifications, such as phosphorylation. Here, we perform an integrated proteomic and glycoproteomic analysis of 83 prospectively collected high-grade serous ovarian carcinoma (HGSC) and 23 non-tumor tissues. Integration of the expression data from global proteomics and glycoproteomics reveals tumor-specific glycosylation, uncovers different glycosylation associated with three tumor clusters, and identifies glycosylation enzymes that were correlated with the altered glycosylation. In addition to providing a valuable resource, these results provide insights into the potential roles of glycosylation in the pathogenesis of HGSC, with the possibility of distinguishing pathological outcomes of ovarian tumors from non-tumors, as well as classifying tumor clusters.

Esophageal squamous cell carcinoma (ESCC) is the most common histological subtype of esophageal cancer in India. Cigarette smoking and chewing tobacco are known risk factors associated with ESCC. However, genomic alterations associated with ESCC in India are not well-characterized. In this study, we carried out exome sequencing to characterize the mutational landscape of ESCC tumors from subjects with a varied history of tobacco usage. Whole exome sequence analysis of ESCC from an Indian cohort revealed several genes that were mutated or had copy number changes. ESCC from tobacco chewers had a higher frequency of C:G > A:T transversions and 2-fold enrichment for mutation signature 4 compared to smokers and non-users of tobacco. Genes, such as TP53, CSMD3, SYNE1, PIK3CA, and NOTCH1 were found to be frequently mutated in Indian cohort. Mutually exclusive mutation patterns were observed in PIK3CA–NOTCH1, DNAH5–ZFHX4, MUC16–FAT1, and ZFHX4–NOTCH1 gene pairs. Recurrent amplifications were observed in 3q22-3q29, 11q13.3-q13.4, 7q22.1-q31.1, and 8q24 regions. Approximately 53% of tumors had genomic alterations in PIK3CA making this pathway a promising candidate for targeted therapy. In conclusion, we observe enrichment of mutation signature 4 in ESCC tumors from patients with a history of tobacco chewing. This is likely due to direct exposure of esophagus to tobacco carcinogens when it is chewed and swallowed. Genomic alterations were frequently observed in PIK3CA-AKT pathway members independent of the history of tobacco usage. PIK3CA pathway can be potentially targeted in ESCC which currently has no effective targeted therapeutic options.

The large majority of cases with intellectual disability are syndromic (i.e. occur with other well-defined clinical phenotypes) and have been studied extensively. Autosomal recessive nonsyndromic intellectual disability is a group of genetically heterogeneous disorders for which a number of potentially causative genes have been identified although the molecular basis of most of them remains unexplored. Here, we report the clinical characteristics and genetic findings of a family with two male siblings affected with autosomal recessive nonsyndromic intellectual disability. Whole exome sequencing was carried out on two affected male siblings and unaffected parents. A potentially pathogenic variant identified in this study was confirmed by Sanger sequencing to be inherited in an autosomal recessive fashion. We identified a novel nonsense mutation (p.Gln368Ter) in the LINS1 gene which leads to loss of 389 amino acids in the C-terminus of the encoded protein. The truncation mutation causes a complete loss of LINES_C domain along with loss of three known phosphorylation sites and a known ubiquitylation site in addition to other evolutionarily conserved regions of LINS1. LINS1 has been reported to cause MRT27 (mental retardation, autosomal recessive 27), a rare autosomal recessive nonsyndromic intellectual disability, with limited characterization of the phenotype. Identification of a potentially pathogenic truncating mutation in LINS1 in two profoundly intellectually impaired patients also confirms its role in cognition.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is accountable for the protracted COVID-19 pandemic. Its high transmission rate and pathogenicity led to health emergencies and economic crisis. Recent studies pertaining to the understanding of the molecular pathogenesis of SARS-CoV-2 infection exhibited the indispensable role of ion channels in viral infection inside the host. Moreover, machine learning (ML)-based algorithms are providing a higher accuracy for host-SARS-CoV-2 protein–protein interactions (PPIs). In this study, PPIs of SARS-CoV-2 proteins with human ion channels (HICs) were trained on the PPI-MetaGO algorithm. PPI networks (PPINs) and a signaling pathway map of HICs with SARS-CoV-2 proteins were generated. Additionally, various U.S. food and drug administration (FDA)-approved drugs interacting with the potential HICs were identified. The PPIs were predicted with 82.71% accuracy, 84.09% precision, 84.09% sensitivity, 0.89 AUC-ROC, 65.17% Matthews correlation coefficient score (MCC) and 84.09% F1 score. Several host pathways were found to be altered, including calcium signaling and taste transduction pathway. Potential HICs could serve as an initial set to the experimentalists for further validation. The study also reinforces the drug repurposing approach for the development of host directed antiviral drugs that may provide a better therapeutic management strategy for infection caused by SARS-CoV-2.

Abstract We assembled the sequences from deep RNA sequencing experiments by the Genotype-Tissue Expression (GTEx) project, to create a new catalog of human genes and transcripts, called CHESS. The new database contains 42,611 genes, of which 20,352 are potentially protein-coding and 22,259 are noncoding, and a total of 323,258 transcripts. These include 224 novel protein-coding genes and 116,156 novel transcripts. We detected over 30 million additional transcripts at more than 650,000 genomic loci, nearly all of which are likely nonfunctional, revealing a heretofore unappreciated amount of transcriptional noise in human cells. The CHESS database is available at http://ccb.jhu.edu/chess.

Unfortunately, after publication of this article [1], errors were noticed in Figs. 3 and 4.

This article describes the whole genome sequencing data from 5 extrapulmonary tuberculosis clinical isolates. The whole genome sequencing was carried out on Illumina MiSeq platform to identify single nucleotide variations (SNVs) associated with drug resistance. A total of 214 SNVs in the coding and promoter regions were identified in the whole genome sequencing analysis. Among the identified SNVs, 18 SNVs were identified in genes known to be associated with first and second line drug resistance. The data is related to the research article “Whole genome sequencing of Mycobacterium tuberculosis isolates from extrapulmonary sites” (Sharma et al., 2017) [1].

Abstract Background Cerebrospinal fluid (CSF) is an important source of potential biomarkers that affect the brain. Biomarkers for neurodegenerative disorders are needed to assist in diagnosis, monitoring disease progression and evaluating efficacy of therapies. Recent studies have demonstrated the involvement of tyrosine kinases in neuronal cell death. Thus, neurodegeneration in the brain is related to altered tyrosine phosphorylation of proteins in the brain and identification of abnormally phosphorylated tyrosine peptides in CSF has the potential to ascertain candidate biomarkers for neurodegenerative disorders. Methods In this study, we used an antibody-based tyrosine phosphopeptide enrichment method coupled with high resolution Orbitrap Fusion Tribrid Lumos Fourier transform mass spectrometer to catalog tyrosine phosphorylated peptides from cerebrospinal fluid. The subset of identified tyrosine phosphorylated peptides was also validated using parallel reaction monitoring (PRM)-based targeted approach. Results To date, there are no published studies on global profiling of phosphotyrosine modifications of CSF proteins. We carried out phosphotyrosine profiling of CSF using an anti-phosphotyrosine antibody-based enrichment and analysis using high resolution Orbitrap Fusion Lumos mass spectrometer. We identified 111 phosphotyrosine peptides mapping to 66 proteins, which included 24 proteins which have not been identified in CSF previously. We then validated a set of 5 tyrosine phosphorylated peptides in an independent set of CSF samples from cognitively normal subjects, using a PRM-based targeted approach. Conclusions The findings from this deep phosphotyrosine profiling of CSF samples have the potential to identify novel disease-related phosphotyrosine-containing peptides in CSF.

Abstract Background Cancer-associated fibroblasts (CAFs) are one of the most important components of tumor stroma and play a key role in modulating tumor growth. However, a mechanistic understanding of how CAFs communicate with tumor cells to promote their proliferation and invasion is far from complete. A major reason for this is that most current techniques and model systems do not capture the complexity of signal transduction that occurs between CAFs and tumor cells. Methods In this study, we employed a stable isotope labeling with amino acids in cell culture (SILAC) strategy to label invasive breast cancer cells, MDA-MB-231, and breast cancer patient-derived CAF cells. We used an antibody-based phosphotyrosine peptide enrichment method coupled to LC–MS/MS to catalog and quantify tyrosine phosphorylation-mediated signal transduction events induced by the bidirectional communication between patient-derived CAFs and tumor cells. Results We discovered that distinct signaling events were activated in CAFs and in tumor epithelial cells during the crosstalk between these two cell types. We identified reciprocal activation of a number of receptor tyrosine kinases including EGFR, FGFR1 and EPHA2 induced by this bidirectional communication. Conclusions Our study not only provides insights into the mechanisms of the interaction between CAFs and tumor cells, but the model system described here could be used as a prototype for analysis of intercellular communication in many different tumor microenvironments.