Machine Learning-Based Fragment Selection Improves the Performance of Qualitative PRM Assays

Targeted mass spectrometry-based platforms have become a valuable tool for the sensitive and specific detection of protein biomarkers in clinical and research settings. Traditionally, developing a targeted assay for peptide quantification has involved manually preselecting several fragment ions and establishing a limit of detection (LOD) and a lower limit of quantitation (LLOQ) for confident detection of the target. Established thresholds such as LOD and LLOQ, however, inherently sacrifice sensitivity to afford specificity. Here, we demonstrate that machine learning can be applied to qualitative PRM assays to discriminate positive from negative samples more effectively than a traditional approach utilizing conventional methods. To demonstrate the utility of this method, we trained an ensemble machine learning model using 282 SARS-CoV-2 positive and 994 SARS-CoV-2 negative nasopharyngeal swabs (NP swab) analyzed using a targeted PRM method. This model was then validated using an independent set of 200 positive and 150 negative samples and achieved a sensitivity of 92% relative to results obtained by RT-PCR, which was superior to a traditional approach that resulted in 86.5% sensitivity when analyzing the same data. These results demonstrate that machine learning can be applied to qualitative PRM assays and results in superior performance relative to traditional methods.

Comparison of anti-peptide and anti-protein antibody-based purification techniques for detection of SARS-CoV-2 by targeted LC-MS/MS

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.

Targeted Detection of SARS-CoV-2 Nucleocapsid Sequence Variants by Mass Spectrometric Analysis of Tryptic Peptides

COVID-19 vaccines are becoming more widely available, but accurate and rapid testing remains a crucial tool for slowing the spread of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus. Although the quantitative reverse transcription-polymerase chain reaction (qRT-PCR) remains the most prevalent testing methodology, numerous tests have been developed that are predicated on detection of the SARS-CoV-2 nucleocapsid protein, including liquid chromatography-tandem mass spectrometry (LC-MS/MS) and immunoassay-based approaches. The continuing emergence of SARS-CoV-2 variants has complicated these approaches, as both qRT-PCR and antigen detection methods can be prone to missing viral variants. In this study, we describe several COVID-19 cases where we were unable to detect the expected peptide targets from clinical nasopharyngeal swabs. Whole genome sequencing revealed that single nucleotide polymorphisms in the gene encoding the viral nucleocapsid protein led to sequence variants that were not monitored in the targeted assay. Minor modifications to the LC-MS/MS method ensured detection of the variants of the target peptide. Additional nucleocapsid variants could be detected by performing the bottom-up proteomic analysis of whole viral genome-sequenced samples. This study demonstrates the importance of considering variants of SARS-CoV-2 in the assay design and highlights the flexibility of mass spectrometry-based approaches to detect variants as they evolve.

A SISCAPA-based approach for detection of SARS-CoV-2 viral antigens from clinical samples

SARS-CoV-2, a novel human coronavirus, has created a global disease burden infecting > 100 million humans in just over a year. RT-PCR is currently the predominant method of diagnosing this viral infection although a variety of tests to detect viral antigens have also been developed. In this study, we adopted a SISCAPA-based enrichment approach using anti-peptide antibodies generated against peptides from the nucleocapsid protein of SARS-CoV-2. We developed a targeted workflow in which nasopharyngeal swab samples were digested followed by enrichment of viral peptides using the anti-peptide antibodies and targeted parallel reaction monitoring (PRM) analysis using a high-resolution mass spectrometer. This workflow was applied to 41 RT-PCR-confirmed clinical SARS-CoV-2 positive nasopharyngeal swab samples and 30 negative samples. The workflow employed was highly specific as none of the target peptides were detected in negative samples. Further, the detected peptides showed a positive correlation with the viral loads as measured by RT-PCR Ct values. The SISCAPA-based platform described in the current study can serve as an alternative method for SARS-CoV-2 viral detection and can also be applied for detecting other microbial pathogens directly from clinical samples.

Acute Kidney Injury in Severe COVID-19 Has Similarities to Sepsis-Associated Kidney Injury: A Multi-Omics Study

OBJECTIVE

To compare coronavirus disease 2019 (COVID-19) acute kidney injury (AKI) to sepsis-AKI (S-AKI). The morphology and transcriptomic and proteomic characteristics of autopsy kidneys were analyzed.

PATIENTS AND METHODS

Individuals 18 years of age and older who died from COVID-19 and had an autopsy performed at Mayo Clinic between April 2020 to October 2020 were included. Morphological evaluation of the kidneys of 17 individuals with COVID-19 was performed. In a subset of seven COVID-19 cases with postmortem interval of less than or equal to 20 hours, ultrastructural and molecular characteristics (targeted transcriptome and proteomics analyses of tubulointerstitium) were evaluated. Molecular characteristics were compared with archived cases of S-AKI and nonsepsis causes of AKI.

RESULTS

The spectrum of COVID-19 renal pathology included macrophage-dominant microvascular inflammation (glomerulitis and peritubular capillaritis), vascular dysfunction (peritubular capillary congestion and endothelial injury), and tubular injury with ultrastructural evidence of mitochondrial damage. Investigation of the spatial architecture using a novel imaging mass cytometry revealed enrichment of CD3⁺CD4⁺ T cells in close proximity to antigen-presenting cells, and macrophage-enriched glomerular and interstitial infiltrates, suggesting an innate and adaptive immune tissue response. Coronavirus disease 2019 AKI and S-AKI, as compared to nonseptic AKI, had an enrichment of transcriptional pathways involved in inflammation (apoptosis, autophagy, major histocompatibility complex class I and II, and type 1 T helper cell differentiation). Proteomic pathway analysis showed that COVID-19 AKI and to a lesser extent S-AKI were enriched in necroptosis and sirtuin-signaling pathways, both involved in regulatory response to inflammation. Upregulation of the ceramide-signaling pathway and downregulation of oxidative phosphorylation in COVID-19 AKI were noted.

CONCLUSION

This data highlights the similarities between S-AKI and COVID-19 AKI and suggests that mitochondrial dysfunction may play a pivotal role in COVID-19 AKI. This data may allow the development of novel diagnostic and therapeutic targets.

Maternal serum lipidomics identifies lysophosphatidic acid as a predictor of small for gestational age neonates

To discover lipidomic alterations during pregnancy in mothers who subsequently delivered small for gestational age (SGA) neonates and identify predictive lipid markers that can help recognize and manage these mothers, we carried out untargeted lipidomics on maternal serum samples collected between 24-28 weeks of gestation. We used a nested case-control study design and serum from mothers who delivered SGA and appropriate for gestational age babies. We applied untargeted lipidomics using mass spectrometry to characterize lipids and discover changes associated with SGA births during pregnancy. Multivariate pattern recognition software Collaborative Laboratory Integrated Reports (CLIR) was used for the post-analytical recognition of range differences in lipid ratios that could differentiate between SGA and control mothers and their integration for complete separation between the two groups. Here, we report changes in lipids from serum collected during pregnancy in mothers who delivered SGA neonates. In contrast to normal pregnancies where lysophosphatidic acid increased over the course of the pregnancy owing to increased activity of lysophospholipase D, we observed a decrease (32%; P = 0.05) of 20:4-lysophosphatidic acid in SGA mothers, which could potentially compromise fetal growth and development. Integration of lipid ratios in an interpretive tool (CLIR) could completely separate SGA mothers from controls demonstrating the power of untargeted lipidomic analyses for identifying novel predictive biomarkers. Additional studies are required for further assessment of the lipid biomarkers identified in this report.

Proximity-Dependent Biotinylation to Elucidate the Interactome of TNK2 Nonreceptor Tyrosine Kinase

Nonreceptor tyrosine kinases (NRTKs) represent an important class of signaling molecules driving diverse cellular pathways. Aberrant expression and hyperphosphorylation of TNK2, an NRTK, have been implicated in multiple cancers. However, the exact proteins and cellular events that mediate phenotypic changes downstream of TNK2 are unclear. Biological systems that employ proximity-dependent biotinylation methods, such as BioID, are being increasingly used to map protein-protein interactions, as they provide increased sensitivity in discovering interaction partners. In this study, we employed stable isotope labeling with amino acids in cell culture and BioID coupled to the biotinylation site identification technology (BioSITe) method that we recently developed to quantitatively explore the interactome of TNK2. By performing a controlled comparative analysis between full-length TNK2 and its truncated counterpart, we were able to not only identify site-level biotinylation of previously well-established TNK2 binders and substrates including NCK1, NCK2, CTTN, and STAT3, but also discover several novel TNK2 interacting partners. We also performed co-immunoprecipitation and immunofluorescence analysis to validate the interaction between TNK2 and CLINT1, a novel TNK2 interacting protein. Overall, this work reveals the power of the BioSITe method coupled to BioID and highlights several molecules that warrant further exploration to assess their functional significance in TNK2-mediated signaling.

Quantitative Tyrosine Phosphoproteome Profiling of AXL Receptor Tyrosine Kinase Signaling Network

Simple Summary

AXL is a receptor tyrosine kinase belonging to the TAM (Tyro3, Axl and Mer) family. The AXL protein plays an important role in promoting cancer development, such as proliferation, migration, invasion and survival of cancer cells. In this study, we used mass spectrometry-based proteomics to quantify the cancer signaling regulated by AXL activation. Our study identified more than 1000 phosphotyrosine sites and discovered that activation of AXL can upregulate multiple cancer-promoting and cell migration/invasion-related signaling pathways. We also observed significant crosstalk as evidenced by rapid phosphorylation of multiple receptor tyrosine kinases and protein tyrosine phosphatases, including PTPN11 and PTPRA, upon GAS6 stimulation. These discoveries should serve as a potentially useful resource for studying AXL functions as well as for the development of effective therapeutic options to target AXL.

Abstract

Overexpression and amplification of AXL receptor tyrosine kinase (RTK) has been found in several hematologic and solid malignancies. Activation of AXL can enhance tumor-promoting processes such as cancer cell proliferation, migration, invasion and survival. Despite the important role of AXL in cancer development, a deep and quantitative mapping of its temporal dynamic signaling transduction has not yet been reported. Here, we used a TMT labeling-based quantitative proteomics approach to characterize the temporal dynamics of the phosphotyrosine proteome induced by AXL activation. We identified >1100 phosphotyrosine sites and observed a widespread upregulation of tyrosine phosphorylation induced by GAS6 stimulation. We also detected several tyrosine sites whose phosphorylation levels were reduced upon AXL activation. Gene set enrichment-based pathway analysis indicated the activation of several cancer-promoting and cell migration/invasion-related signaling pathways, including RAS, EGFR, focal adhesion, VEGFR and cytoskeletal rearrangement pathways. We also observed a rapid induction of phosphorylation of protein tyrosine phosphatases, including PTPN11 and PTPRA, upon GAS6 stimulation. The novel molecules downstream of AXL identified in this study along with the detailed global quantitative map elucidating the temporal dynamics of AXL activation should not only help understand the oncogenic role of AXL, but also aid in developing therapeutic options to effectively target AXL.

Proteomic Signature of Host Response to SARS-CoV-2 Infection in the Nasopharynx

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, has become a global health pandemic. COVID-19 severity ranges from an asymptomatic infection to a severe multiorgan disease. Although the inflammatory response has been implicated in the pathogenesis of COVID-19, the exact nature of dysregulation in signaling pathways has not yet been elucidated, underscoring the need for further molecular characterization of SARS-CoV-2 infection in humans. Here, we characterize the host response directly at the point of viral entry through analysis of nasopharyngeal swabs. Multiplexed high-resolution MS-based proteomic analysis of confirmed COVID-19 cases and negative controls identified 7582 proteins and revealed significant upregulation of interferon-mediated antiviral signaling in addition to multiple other proteins that are not encoded by interferon-stimulated genes or well characterized during viral infections. Downregulation of several proteasomal subunits, E3 ubiquitin ligases, and components of protein synthesis machinery was significant upon SARS-CoV-2 infection. Targeted proteomics to measure abundance levels of MX1, ISG15, STAT1, RIG-I, and CXCL10 detected proteomic signatures of interferon-mediated antiviral signaling that differentiated COVID-19-positive from COVID-19-negative cases. Phosphoproteomic analysis revealed increased phosphorylation of several proteins with known antiviral properties as well as several proteins involved in ciliary function (CEP131 and CFAP57) that have not previously been implicated in the context of coronavirus infections. In addition, decreased phosphorylation levels of AKT and PKC, which have been shown to play varying roles in different viral infections, were observed in infected individuals relative to controls. These data provide novel insights that add depth to our understanding of SARS-CoV-2 infection in the upper airway and establish a proteomic signature for this viral infection.

DIA-Based Proteome Profiling of Nasopharyngeal Swabs from COVID-19 Patients

Since the recent outbreak of COVID-19, there have been intense efforts to understand viral pathogenesis and host immune response to combat SARS-CoV-2. It has become evident that different host alterations can be identified in SARS-CoV-2 infection based on whether infected cells, animal models or clinical samples are studied. Although nasopharyngeal swabs are routinely collected for SARS-CoV-2 detection by RT-PCR testing, host alterations in the nasopharynx at the proteomic level have not been systematically investigated. Thus, we sought to characterize the host response through global proteome profiling of nasopharyngeal swab specimens. A mass spectrometer combining trapped ion mobility spectrometry (TIMS) and high-resolution QTOF mass spectrometer with parallel accumulation-serial fragmentation (PASEF) was deployed for unbiased proteome profiling. First, deep proteome profiling of pooled nasopharyngeal swab samples was performed in the PASEF enabled DDA mode, which identified 7723 proteins that were then used to generate a spectral library. This approach provided peptide level evidence of five missing proteins for which MS/MS spectrum and mobilograms were validated with synthetic peptides. Subsequently, quantitative proteomic profiling was carried out for 90 individual nasopharyngeal swab samples (45 positive and 45 negative) in DIA combined with PASEF, termed as diaPASEF mode, which resulted in a total of 5023 protein identifications. Of these, 577 proteins were found to be upregulated in SARS-CoV-2 positive samples. Functional analysis of these upregulated proteins revealed alterations in several biological processes including innate immune response, viral protein assembly, and exocytosis. To the best of our knowledge, this study is the first to deploy diaPASEF for quantitative proteomic profiling of clinical samples and shows the feasibility of adopting such an approach to understand mechanisms and pathways altered in diseases.

High-resolution mass spectrometric analysis of cardiolipin profiles in Barth syndrome

Barth syndrome is an X-linked recessive disorder caused by pathogenic variants in TAZ, which leads to a reduction in cardiolipin with a concomitant elevation of monolysocardiolipins. There is a paucity of studies characterizing changes in individual species of monolysocardiolipins, dilysocardiolipins and cardiolipin in Barth syndrome using high resolution untargeted lipidomics that can accurately annotate and quantify diverse lipids. We confirmed the structural diversity monolysocardiolipins, dilysocardiolipins and cardiolipin and identified individual species that showed previously unreported alterations in BTHS. Development of mass spectrometry-based targeted assays for these lipid biomarkers should provide an important tool for clinical diagnosis of Barth syndrome.

Analytical sensitivity and specificity of four point of care rapid antigen diagnostic tests for SARS-CoV-2 using real-time quantitative PCR, quantitative droplet digital PCR, and a mass spectrometric antigen assay as comparator methods

BACKGROUND

We evaluated the analytical sensitivity and specificity of four rapid antigen diagnostic tests (Ag RDTs) for SARS-CoV-2, using reverse transcription quantitative PCR (RT-qPCR) as the reference method; and further characterizing samples using droplet digital quantitative PCR (ddPCR) and a mass spectrometric antigen test.

METHODS

350 (150 negative and 200 RT-qPCR positive) residual phosphate buffered saline (PBS) samples were tested for antigen using the BD Veritor lateral flow (LF), ACON LF, ACON fluorescence immunoassay (FIA), and LumiraDx FIA. ddPCR was performed on RT-qPCR positive samples to quantitate the viral load in copies/mL applied to each Ag RDT. Mass spectrometric antigen testing was performed on PBS samples to obtain a set of RT-qPCR positive, antigen positive samples for further analysis.

RESULTS

All Ag RDTs had nearly 100% specificity compared to RT-qPCR. Overall analytical sensitivity varied from 66.5% to 88.3%. All methods detected antigen in samples with viral load >1,500,000 copies/mL RNA, and detected ≥75% of samples with viral load of 500,000 to 1,500,000 copies/mL. The BD Veritor LF detected only 25% of samples with viral load between 50,000-500,000 copies/mL, compared to 75% for the ACON LF device and >80% for LumiraDx and ACON FIA. The ACON FIA detected significantly more samples with viral load <50,000 copies/mL compared to the BD Veritor. Among samples with detectable antigen and viral load <50,000 copies/mL, sensitivity of the Ag RDT varied between 13.0% (BD Veritor) and 78.3% (ACON FIA).

CONCLUSIONS

Ag RDTs differ significantly in analytical sensitivity, particularly at viral load <500,000 copies/mL.

A mass spectrometry-based targeted assay for detection of SARS-CoV-2 antigen from clinical specimens

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.

Mapping the micro-proteome of the nuclear lamina and lamina-associated domains

The nuclear lamina is a proteinaceous network of filaments that provide both structural and gene regulatory functions by tethering proteins and large domains of DNA, the so-called lamina-associated domains (LADs), to the periphery of the nucleus. LADs are a large fraction of the mammalian genome that are repressed, in part, by their association to the nuclear periphery. The genesis and maintenance of LADs is poorly understood as are the proteins that participate in these functions. In an effort to identify proteins that reside at the nuclear periphery and potentially interact with LADs, we have taken a two-pronged approach. First, we have undertaken an interactome analysis of the inner nuclear membrane bound LAP2β to further characterize the nuclear lamina proteome. To accomplish this, we have leveraged the BioID system, which previously has been successfully used to characterize the nuclear lamina proteome. Second, we have established a system to identify proteins that bind to LADs by developing a chromatin-directed BioID system. We combined the BioID system with the m6A-tracer system which binds to LADs in live cells to identify both LAD proximal and nuclear lamina proteins. In combining these datasets, we have further characterized the protein network at the nuclear lamina, identified putative LAD proximal proteins and found several proteins that appear to interface with both micro-proteomes. Importantly, several proteins essential for LAD function, including heterochromatin regulating proteins related to H3K9 methylation, were identified in this study.

Quantitative Proteomics Reveals that the OGT Interactome Is Remodeled in Response to Oxidative Stress

The dynamic modification of specific serine and threonine residues of intracellular proteins by O-linked N-acetyl-β-D-glucosamine (O-GlcNAc) mitigates injury and promotes cytoprotection in a variety of stress models. The O-GlcNAc transferase (OGT) and the O-GlcNAcase are the sole enzymes that add and remove O-GlcNAc, respectively, from thousands of substrates. It remains unclear how just two enzymes can be specifically controlled to affect glycosylation of target proteins and signaling pathways both basally and in response to stress. Several lines of evidence suggest that protein interactors regulate these responses by affecting OGT and O-GlcNAcase activity, localization, and substrate specificity. To provide insight into the mechanisms by which OGT function is controlled, we have used quantitative proteomics to define OGT's basal and stress-induced interactomes. OGT and its interaction partners were immunoprecipitated from OGT WT, null, and hydrogen peroxide-treated cell lysates that had been isotopically labeled with light, medium, and heavy lysine and arginine (stable isotopic labeling of amino acids in cell culture). In total, more than 130 proteins were found to interact with OGT, many of which change their association upon hydrogen peroxide stress. These proteins include the major OGT cleavage and glycosylation substrate, host cell factor 1, which demonstrated a time-dependent dissociation after stress. To validate less well-characterized interactors, such as glyceraldehyde 3-phosphate dehydrogenase and histone deacetylase 1, we turned to parallel reaction monitoring, which recapitulated our discovery-based stable isotopic labeling of amino acids in cell culture approach. Although the majority of proteins identified are novel OGT interactors, 64% of them are previously characterized glycosylation targets that contain varied domain architecture and function. Together these data demonstrate that OGT interacts with unique and specific interactors in a stress-responsive manner.

Transcriptomic Profiles of Confirmed Pediatric Tuberculosis Patients and Household Contacts Identifies Active Tuberculosis, Infection, and Treatment Response Among Indian Children

BACKGROUND

Gene expression profiling is emerging as a tool for tuberculosis diagnosis and treatment response monitoring, but limited data specific to Indian children and incident tuberculosis infection (TBI) exist.

METHODS

Sixteen pediatric Indian tuberculosis cases were age- and sex-matched to 32 tuberculosis-exposed controls (13 developed incident TBI without subsequent active tuberculosis). Longitudinal samples were collected for ribonucleic acid sequencing. Differential expression analysis generated gene lists that identify tuberculosis diagnosis and tuberculosis treatment response. Data were compared with published gene lists. Population-specific risk score thresholds were calculated.

RESULTS

Seventy-one genes identified tuberculosis diagnosis and 25 treatment response. Within-group expression was partially explained by age, sex, and incident TBI. Transient changes in gene expression were identified after both infection and treatment. Application of 27 published gene lists to our data found variable performance for tuberculosis diagnosis (sensitivity 0.38-1.00, specificity 0.48-0.93) and treatment response (sensitivity 0.70-0.80, specificity 0.40-0.80). Our gene lists found similarly variable performance when applied to published datasets for diagnosis (sensitivity 0.56-0.85, specificity 0.50-0.85) and treatment response (sensitivity 0.49- 0.86, specificity 0.50-0.84).

CONCLUSIONS

Gene expression profiles among Indian children with confirmed tuberculosis were distinct from adult-derived gene lists, highlighting the importance of including distinct populations in differential gene expression models.

Expanding the clinical and metabolic phenotype of DPM2 deficient congenital disorders of glycosylation

Pathogenic alterations in the DPM2 gene have been previously described in patients with hypotonia, progressive muscle weakness, absent psychomotor development, intractable seizures, and early death. We identified biallelic DPM2 variants in a 23-year-old male with truncal hypotonia, hypertonicity, congenital heart defects, intellectual disability, and generalized muscle wasting. His clinical presentation was much less severe than that of the three previously described patients. This is the second report on this ultra-rare disorder. Here we review the characteristics of previously reported individuals with a defect in the DPM complex while expanding the clinical phenotype of DPM2-Congenital Disorders of Glycosylation. In addition, we offer further insights into the pathomechanism of DPM2-CDG disorder by introducing glycomics and lipidomics analysis.

Cerebrospinal fluid lipidomics for biomarkers of Alzheimer's disease

Alzheimer's disease (AD) is the most common cause of dementia and is associated with serious neurologic sequelae resulting from neurodegenerative changes. Identification of markers of early-stage AD could be important for designing strategies to arrest the progression of the disease. The brain is rich in lipids because they are crucial for signal transduction and anchoring of membrane proteins. Cerebrospinal fluid (CSF) is an excellent specimen for studying the metabolism of lipids in AD because it can reflect changes occurring in the brain. We aimed to identify CSF lipidomic alterations associated with AD, using untargeted lipidomics, carried out in positive and negative ion modes. We found CSF lipids that were significantly altered in AD cases. In addition, comparison of CSF lipid profiles between persons with mild cognitive impairment (MCI) and AD showed a strong positive correlation between the lipidomes of the MCI and AD groups. The novel lipid biomarkers identified in this study are excellent candidates for validation in a larger set of patient samples and as predictive biomarkers of AD through future longitudinal studies. Once validated, the lipid biomarkers could lead to early detection, disease monitoring and the ability to measure the efficacy of potential therapeutic interventions in AD.

Mutation-Specific and Common Phosphotyrosine Signatures of KRAS G12D and G13D Alleles

KRAS is one of the most frequently mutated genes across all cancer subtypes. Two of the most frequent oncogenic KRAS mutations observed in patients result in glycine to aspartic acid substitution at either codon 12 (G12D) or 13 (G13D). Although the biochemical differences between these two predominant mutations are not fully understood, distinct clinical features of the resulting tumors suggest involvement of disparate signaling mechanisms. When we compared the global phosphotyrosine proteomic profiles of isogenic colorectal cancer cell lines bearing either G12D or G13D KRAS mutation, we observed both shared as well as unique signaling events induced by the two KRAS mutations. Remarkably, while the G12D mutation led to an increase in membrane proximal and adherens junction signaling, the G13D mutation led to activation of signaling molecules such as nonreceptor tyrosine kinases, MAPK kinases, and regulators of metabolic processes. The importance of one of the cell surface molecules, MPZL1, which was found to be hyperphosphorylated in G12D cells, was confirmed by cellular assays as its knockdown led to a decrease in proliferation of G12D but not G13D expressing cells. Overall, our study reveals important signaling differences across two common KRAS mutations and highlights the utility of our approach to systematically dissect subtle differences between related oncogenic mutants and potentially lead to individualized treatments.

Signature Fragment Ions of Biotinylated Peptides

The use of biotin or biotin-containing reagents is an essential component of many protein purification and labeling technologies. Owing to its small size and high affinity to the avidin family of proteins, biotin is a versatile molecular handle that permits both enrichment and purity that is not easily achieved by other reagents. Traditionally, the use of biotinylation to enrich for proteins has not required the detection of the site of biotinylation. However, newer technologies for discovery of protein-protein interactions, such as APEX and BioID, as well as some of the click chemistry-based labeling approaches have underscored the importance of determining the exact residue that is modified by biotin. Anti-biotin antibody-based enrichment of biotinylated peptides (e.g., BioSITe) coupled to LC-MS/MS permit large-scale detection and localization of sites of biotinylation. As with any chemical modification of peptides, understanding the fragmentation patterns that result from biotin modification is essential to improving its detection by LC-MS/MS. Tandem mass spectra of biotinylated peptides has not yet been studied systematically. Here, we describe the various signature fragment ions generated with collision-induced dissociation of biotinylated peptides. We focused on biotin adducts attached to peptides generated by BioID and APEX experiments, including biotin, isotopically heavy biotin, and biotin-XX-phenol, a nonpermeable variant of biotin-phenol. We also highlight how the detection of biotinylated peptides in high-throughput studies poses certain computational challenges for accurate quantitation which need to be addressed. Our findings about signature fragment ions of biotinylated peptides should be helpful in the confirmation of biotinylation sites.

Hotspot SF3B1 mutations induce metabolic reprogramming and vulnerability to serine deprivation

Cancer-associated mutations in the spliceosome gene SF3B1 create a neomorphic protein that produces aberrant mRNA splicing in hundreds of genes, but the ensuing biologic and therapeutic consequences of this missplicing are not well understood. Here we have provided evidence that aberrant splicing by mutant SF3B1 altered the transcriptome, proteome, and metabolome of human cells, leading to missplicing-associated downregulation of metabolic genes, decreased mitochondrial respiration, and suppression of the serine synthesis pathway. We also found that mutant SF3B1 induces vulnerability to deprivation of the nonessential amino acid serine, which was mediated by missplicing-associated downregulation of the serine synthesis pathway enzyme PHGDH. This vulnerability was manifest both in vitro and in vivo, as dietary restriction of serine and glycine in mice was able to inhibit the growth of SF3B1MUT xenografts. These findings describe a role for SF3B1 mutations in altered energy metabolism, and they offer a new therapeutic strategy against SF3B1MUT cancers.

Integrated Transcriptomic and Proteomic Analysis of Primary Human Umbilical Vein Endothelial Cells

Understanding the molecular profile of every human cell type is essential for understanding its role in normal physiology and disease. Technological advancements in DNA sequencing, mass spectrometry, and computational methods allow us to carry out multiomics analyses although such approaches are not routine yet. Human umbilical vein endothelial cells (HUVECs) are a widely used model system to study pathological and physiological processes associated with the cardiovascular system. In this study, next-generation sequencing and high-resolution mass spectrometry to profile the transcriptome and proteome of primary HUVECs is employed. Analysis of 145 million paired-end reads from next-generation sequencing confirmed expression of 12 186 protein-coding genes (FPKM ≥0.1), 439 novel long non-coding RNAs, and revealed 6089 novel isoforms that were not annotated in GENCODE. Proteomics analysis identifies 6477 proteins including confirmation of N-termini for 1091 proteins, isoforms for 149 proteins, and 1034 phosphosites. A database search to specifically identify other post-translational modifications provide evidence for a number of modification sites on 117 proteins which include ubiquitylation, lysine acetylation, and mono-, di- and tri-methylation events. Evidence for 11 "missing proteins," which are proteins for which there was insufficient or no protein level evidence, is provided. Peptides supporting missing protein and novel events are validated by comparison of MS/MS fragmentation patterns with synthetic peptides. Finally, 245 variant peptides derived from 207 expressed proteins in addition to alternate translational start sites for seven proteins and evidence for novel proteoforms for five proteins resulting from alternative splicing are identified. Overall, it is believed that the integrated approach employed in this study is widely applicable to study any primary cell type for deeper molecular characterization.

Surgery, Octreotide, Temozolomide, Bevacizumab, Radiotherapy, and Pegvisomant Treatment of an AIP Mutation‒Positive Child

CONTEXT

Inactivating germline mutations in the aryl hydrocarbon receptor interacting protein (AIP) gene are linked to pituitary adenoma predisposition. Here, we present the youngest known patient with AIP-related pituitary adenoma.

CASE DESCRIPTION

The patient presented at the age of 4 years with pituitary apoplexy and left ptosis with severe visual loss following a 1-year history of abdominal pain, headaches, and rapid growth. His IGF-1 level was 5× the upper limit of normal, and his random GH level was 1200 ng/mL. MRI showed a 43 × 24 × 35‒mm adenoma with suprasellar extension invading the left cavernous sinus (Knosp grade 4). After transsphenoidal surgery, histology showed a grade 2A sparsely granulated somatotropinoma with negative O6-methylguanine-DNA methyltransferase and positive vascular endothelial growth factor staining. Genetic testing identified a heterozygous germline nonsense AIP mutation (p.Arg81Ter). Exome sequencing of the tumor revealed that it had lost the entire maternal chromosome-11, rendering it hemizygous for chromosome-11 and therefore lacking functional copies of AIP in the tumor. He was started on octreotide, but because the tumor rapidly regrew and IGF-1 levels were unchanged, temozolomide was initiated, and intensity-modulated radiotherapy was administered 5 months after surgery. Two months later, bevacizumab was added, resulting in excellent tumor response. Although these treatments stabilized tumor growth over 4 years, IGF-1 was normalized only after pegvisomant treatment, although access to this medication was intermittent. At 3.5 years of follow-up, gamma knife treatment was administered, and pegvisomant dose increase was indicated.

CONCLUSION

Multimodal treatment with surgery, long-acting octreotide, radiotherapy, temozolomide, bevacizumab, and pegvisomant can control genetically driven, aggressive, childhood-onset somatotropinomas.

Integrated Transcriptomic and Proteomic Analysis of Human Eccrine Sweat Glands Identifies Missing and Novel Proteins

The eccrine sweat gland is an exocrine gland that is involved in the secretion of sweat for control of temperature. Malfunction of the sweat glands can result in disorders such as miliaria, hyperhidrosis and bromhidrosis. Understanding the transcriptome and proteome of sweat glands is important for understanding their physiology and role in diseases. However, no systematic transcriptome or proteome analysis of sweat glands has yet been reported. Here, we isolated eccrine sweat glands from human skin by microdissection and performed RNA-seq and proteome analysis. In total, ∼138,000 transcripts and ∼6,100 proteins were identified. Comparison of the RNA-seq data of eccrine sweat glands to other human tissues revealed the closest resemblance to the cortex region of kidneys. The proteome data showed enrichment of proteins involved in secretion, reabsorption, and wound healing. Importantly, protein level identification of the calcium ion channel TRPV4 suggests the importance of eccrine sweat glands in re-epithelialization of wounds and prevention of dehydration. We also identified 2 previously missing proteins from our analysis. Using a proteogenomic approach, we identified 7 peptides from 5 novel genes, which we validated using synthetic peptides. Most of the novel proteins were from short open reading frames (sORFs) suggesting that many sORFs still remain to be annotated in the human genome. This study presents the first integrated analysis of the transcriptome and proteome of the human eccrine sweat gland and would become a valuable resource for studying sweat glands in physiology and disease.

Family-Based Next-Generation Sequencing Study Identifies an IL2RG Variant in an Infant with Primary Immunodeficiency

Primary immunodeficiencies (PIDs) are a rare and heterogeneous group of inherited genetic disorders that are characterized by an absent or impaired immune system. In this report, we describe the use of next-generation sequencing to investigate a male infant with clinical and immunological manifestations suggestive of a PID. Whole-exome sequencing of the infant along with his parents revealed a novel nucleotide variant (cytosine to adenine substitution at nucleotide position 252) in the coding region of the interleukin 2 receptor subunit gamma (IL2RG) gene. The mother was found to be a carrier. These findings are consistent with a diagnosis of X-linked severe combined immunodeficiency and represent the first such reported mutation in an Indian family. This mutation leads to an asparagine to lysine substitution (p.Asn84Lys) located in the extracellular domain of IL2RG, which is predicted to be pathogenic. Our study demonstrates the power of next-generation sequencing in identifying potential causative mutations to enable accurate clinical diagnosis, prenatal screening, and carrier female detection in PID patients. We believe that this approach, which is not a current routine in clinical practice, will become a mainstream component of individualized medicine in the near future.

Proteomic Analysis of the Human Anterior Pituitary Gland

The pituitary function is regulated by a complex system involving the hypothalamus and biological networks within the pituitary. Although the hormones secreted from the pituitary have been well studied, comprehensive analyses of the pituitary proteome are limited. Pituitary proteomics is a field of postgenomic research that is crucial to understand human health and pituitary diseases. In this context, we report here a systematic proteomic profiling of human anterior pituitary gland (adenohypophysis) using high-resolution Fourier transform mass spectrometry. A total of 2164 proteins were identified in this study, of which 105 proteins were identified for the first time compared with high-throughput proteomic-based studies from human pituitary glands. In addition, we identified 480 proteins with secretory potential and 187 N-terminally acetylated proteins. These are the first region-specific data that could serve as a vital resource for further investigations on the physiological role of the human anterior pituitary glands and the proteins secreted by them. We anticipate that the identification of previously unknown proteins in the present study will accelerate biomedical research to decipher their role in functioning of the human anterior pituitary gland and associated human diseases.

A Next-Generation Sequencing-Based Molecular Approach to Characterize a Tick Vector in Lyme Disease

Next-generation sequencing approaches have revolutionized genomic medicine and enabled rapid diagnosis for several diseases. These approaches are widely used for pathogen detection in several infectious diseases. Lyme disease is a tick-borne infectious disease, which affects multiple organs. The causative organism is a spirochete, Borrelia burgdorferi, which is transmitted by ticks. Lyme disease can be treated easily if detected early, but its diagnosis is often delayed or is incorrect leading to a chronic debilitating condition. Current confirmatory diagnostic tests for Lyme disease rely on detection of antigens derived from B. burgdorferi, which are prone to both false positives and false negatives. Instead of focusing only on the human host for the diagnosis of Lyme disease, one could also attempt to identify the vector (tick) and the causative organism carried by the tick. Since all ticks do not transmit Lyme disease, it can be informative to accurately identify the tick from the site of bite, which is often observed by the patient and discarded. However, identifying ticks based on morphology alone requires a trained operator and can still be incorrect. Thus, we decided to take a molecular approach by sequencing DNA and RNA from a tick collected from an individual bitten by the tick. Using next-generation sequencing, we confirmed the identity of the tick as a dog tick, Dermacentor variabilis, and did not identify any pathogenic bacterial sequences, including Borrelia species. Despite the limited availability of nucleotide sequences for many types of ticks, our approach correctly identified the tick species. This proof-of-principle study demonstrates the potential of next-generation sequencing in the diagnosis of tick-borne infections, which can also be extended to other zoonotic diseases.

Quantitative Proteomic Profiling of Cerebrospinal Fluid to Identify Candidate Biomarkers for Alzheimer's Disease

PURPOSE

The aim of this study is to identify the potential cerebrospinal fluid (CSF) biomarkers for Alzheimer's disease and to evaluate these markers on independent CSF samples using parallel reaction monitoring (PRM) assays.

EXPERIMENTAL DESIGN

High-Resolution mass spectrometry and tandem mass tag (TMT) multiplexing technology are employed to identify potential biomarkers for Alzheimer's disease. Some of the identified potential biomarkers are validated using PRM assays.

RESULTS

A total of 2327 proteins are identified in the CSF of which 139 are observed to be significantly altered in the CSF of AD patients. The proteins altered in AD includes a number of known AD marker such as MAPT, NPTX2, VGF, GFAP, and NCAM1 as well as novel biomarkers such as PKM and YWHAG. These findings are validated in a separate set of CSF specimens from AD dementia patients and controls. NPTX2, in combination with PKM or YWHAG, leads to the best results with AUCs of 0.935 and 0.933, respectively.

CONCLUSIONS AND CLINICAL RELEVANCE

The proteins that are found to be altered in the CSF of patients with AD could be used for monitoring disease progression and therapeutic response and perhaps also for early detection once they are validated in larger studies.

CHESS: a new human gene catalog curated from thousands of large-scale RNA sequencing experiments reveals extensive transcriptional noise

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 .

Phosphoproteomics of Retinoblastoma: A Pilot Study Identifies Aberrant Kinases

Retinoblastoma is a malignant tumour of the retina which most often occurs in children. Earlier studies on retinoblastoma have concentrated on the identification of key players in the disease and have not provided information on activated/inhibited signalling pathways. The dysregulation of protein phosphorylation in cancer provides clues about the affected signalling cascades in cancer. Phosphoproteomics is an ideal tool for the study of phosphorylation changes in proteins. Hence, global phosphoproteomics of retinoblastoma (RB) was carried out to identify signalling events associated with this cancer. Over 350 proteins showed differential phosphorylation in RB compared to control retina. Our study identified stress response proteins to be hyperphosphorylated in RB which included H2A histone family member X (H2AFX) and sirtuin 1. In particular, Ser140 of H2AFX also known as gamma-H2AX was found to be hyperphosphorylated in retinoblastoma, which indicated the activation of DNA damage response pathways. We also observed the activation of anti-apoptosis in retinoblastoma compared to control. These observations showed the activation of survival pathways in retinoblastoma. The identification of hyperphosphorylated protein kinases including Bromodomain containing 4 (BRD4), Lysine deficient protein kinase 1 (WNK1), and Cyclin-dependent kinase 1 (CDK1) in RB opens new avenues for the treatment of RB. These kinases can be considered as probable therapeutic targets for RB, as small-molecule inhibitors for some of these kinases are already in clinical trials for the treatment other cancers.

Proteomic Analysis of the Human Olfactory Bulb

The importance of olfaction to human health and disease is often underappreciated. Olfactory dysfunction has been reported in association with a host of common complex diseases, including neurological diseases such as Alzheimer's disease and Parkinson's disease. For health, olfaction or the sense of smell is also important for most mammals, for optimal engagement with their environment. Indeed, animals have developed sophisticated olfactory systems to detect and interpret the rich information presented to them to assist in day-to-day activities such as locating food sources, differentiating food from poisons, identifying mates, promoting reproduction, avoiding predators, and averting death. In this context, the olfactory bulb is a vital component of the olfactory system receiving sensory information from the axons of the olfactory receptor neurons located in the nasal cavity and the first place that processes the olfactory information. We report in this study original observations on the human olfactory bulb proteome in healthy subjects, using a high-resolution mass spectrometry-based proteomic approach. We identified 7750 nonredundant proteins from human olfactory bulbs. Bioinformatics analysis of these proteins showed their involvement in biological processes associated with signal transduction, metabolism, transport, and olfaction. These new observations provide a crucial baseline molecular profile of the human olfactory bulb proteome, and should assist the future discovery of biomarker proteins and novel diagnostics associated with diseases characterized by olfactory dysfunction.

BioSITe: A Method for Direct Detection and Quantitation of Site-Specific Biotinylation

Biotin-based labeling strategies are widely employed to study protein-protein interactions, subcellular proteomes and post-translational modifications, as well as, used in drug discovery. While the high affinity of streptavidin for biotin greatly facilitates the capture of biotinylated proteins, it still presents a challenge, as currently employed, for the recovery of biotinylated peptides. Here we describe a strategy designated Biotinylation Site Identification Technology (BioSITe) for the capture of biotinylated peptides for LC-MS/MS analyses. We demonstrate the utility of BioSITe when applied to proximity-dependent labeling methods, APEX and BioID, as well as biotin-based click chemistry strategies for identifying O-GlcNAc-modified sites. We demonstrate the use of isotopically labeled biotin for quantitative BioSITe experiments that simplify differential interactome analysis and obviate the need for metabolic labeling strategies such as SILAC. Our data also highlight the potential value of site-specific biotinylation in providing spatial and topological information about proteins and protein complexes. Overall, we anticipate that BioSITe will replace the conventional methods in studies where detection of biotinylation sites is important.

Characterization of human pineal gland proteome

The pineal gland is a neuroendocrine gland located at the center of the brain. It is known to regulate various physiological functions in the body through secretion of the neurohormone melatonin. Comprehensive characterization of the human pineal gland proteome has not been undertaken to date. We employed a high-resolution mass spectrometry-based approach to characterize the proteome of the human pineal gland. A total of 5874 proteins were identified from the human pineal gland in this study. Of these, 5820 proteins were identified from the human pineal gland for the first time. Interestingly, 1136 proteins from the human pineal gland were found to contain a signal peptide domain, which indicates the secretory nature of these proteins. An unbiased global proteomic profile of this biomedically important organ should benefit molecular research to unravel the role of the pineal gland in neuropsychiatric and neurodegenerative diseases.

Mosquito-Borne Diseases and Omics: Tissue-Restricted Expression and Alternative Splicing Revealed by Transcriptome Profiling of Anopheles stephensi

Malaria is one of the most debilitating mosquito-borne diseases with high global health burdens. While much of the research on malaria and mosquito-borne diseases is focused on Africa, Southeast Asia accounts for a sizable portion of the global burden of malaria. Moreover, about 50% of the Asian malaria incidence and deaths have been from India. A promising development in this context is that the completion of genome sequence of Anopheles stephensi, a major malaria vector in Asia, offers new opportunities for global health innovation, including the progress in deciphering the vectorial ability of this mosquito species at a molecular level. Moving forward, tissue-based expression profiling would be the next obvious step in understanding gene functions of An. stephensi. We report in this article, to the best of our knowledge, the first in-depth study on tissue-based transcriptomic profile of four important organs (midgut, Malpighian tubules, fat body, and ovary) of adult female An. stephensi mosquitoes. In all, we identified over 20,000 transcripts corresponding to more than 12,000 gene loci from these four tissues. We present and discuss the tissue-based expression profiles of majority of annotated transcripts in An. stephensi genome, and the dynamics of their alternative splicing in these tissues, in this study. The domain-based Gene Ontology analysis of the differentially expressed transcripts in each of the mosquito tissue indicated enrichment of transcripts with proteolytic activity in midgut; transporter activity in Malpighian tubules; cell cycle, DNA replication, and repair activities in ovaries; and oxidoreductase activities in fat body. Tissue-based study of transcript expression and gene functions markedly enhances our understanding of this important malaria vector, and in turn, offers rationales for further studies on vectorial ability and identification of novel molecular targets to intercept malaria transmission.

Proteogenomics of Candida tropicalis--An Opportunistic Pathogen with Importance for Global Health

The frequency of Candida infections is currently rising, and thus adversely impacting global health. The situation is exacerbated by azole resistance developed by fungal pathogens. Candida tropicalis is an opportunistic pathogen that causes candidiasis, for example, in immune-compromised individuals, cancer patients, and those who undergo organ transplantation. It is a member of the non-albicans group of Candida that are known to be azole-resistant, and is frequently seen in individuals being treated for cancers, HIV-infection, and those who underwent bone marrow transplantation. Although the genome of C. tropicalis was sequenced in 2009, the genome annotation has not been supported by experimental validation. In the present study, we have carried out proteomics profiling of C. tropicalis using high-resolution Fourier transform mass spectrometry. We identified 2743 proteins, thus mapping nearly 44% of the computationally predicted protein-coding genes with peptide level evidence. In addition to identifying 2591 proteins in the cell lysate of this yeast, we also analyzed the proteome of the conditioned media of C. tropicalis culture and identified several unique secreted proteins among a total of 780 proteins. By subjecting the mass spectrometry data derived from cell lysate and conditioned media to proteogenomic analysis, we identified 86 novel genes, 12 novel exons, and corrected 49 computationally-predicted gene models. To our knowledge, this is the first high-throughput proteomics study of C. tropicalis validating predicted protein coding genes and refining the current genome annotation. The findings may prove useful in future global health efforts to fight against Candida infections.

Integrating transcriptomic and proteomic data for accurate assembly and annotation of genomes

Complementing genome sequence with deep transcriptome and proteome data could enable more accurate assembly and annotation of newly sequenced genomes. Here, we provide a proof-of-concept of an integrated approach for analysis of the genome and proteome of Anopheles stephensi, which is one of the most important vectors of the malaria parasite. To achieve broad coverage of genes, we carried out transcriptome sequencing and deep proteome profiling of multiple anatomically distinct sites. Based on transcriptomic data alone, we identified and corrected 535 events of incomplete genome assembly involving 1196 scaffolds and 868 protein-coding gene models. This proteogenomic approach enabled us to add 365 genes that were missed during genome annotation and identify 917 gene correction events through discovery of 151 novel exons, 297 protein extensions, 231 exon extensions, 192 novel protein start sites, 19 novel translational frames, 28 events of joining of exons, and 76 events of joining of adjacent genes as a single gene. Incorporation of proteomic evidence allowed us to change the designation of more than 87 predicted “noncoding RNAs” to conventional mRNAs coded by protein-coding genes. Importantly, extension of the newly corrected genome assemblies and gene models to 15 other newly assembled Anopheline genomes led to the discovery of a large number of apparent discrepancies in assembly and annotation of these genomes. Our data provide a framework for how future genome sequencing efforts should incorporate transcriptomic and proteomic analysis in combination with simultaneous manual curation to achieve near complete assembly and accurate annotation of genomes.

Proteomic profiling of retinoblastoma by high resolution mass spectrometry

Background

Retinoblastoma is an ocular neoplastic cancer caused primarily due to the mutation/deletion of RB1 gene. Due to the rarity of the disease very limited information is available on molecular changes in primary retinoblastoma. High throughput analysis of retinoblastoma transcriptome is available however the proteomic landscape of retinoblastoma remains unexplored. In the present study we used high resolution mass spectrometry-based quantitative proteomics to identify proteins associated with pathogenesis of retinoblastoma.

Methods

We used five pooled normal retina and five pooled retinoblastoma tissues to prepare tissue lysates. Equivalent amount of proteins from each group was trypsin digested and labeled with iTRAQ tags. The samples were analyzed on Orbitrap Velos mass spectrometer. We further validated few of the differentially expressed proteins by immunohistochemistry on primary tumors.

Results

We identified and quantified a total of 3587 proteins in retinoblastoma when compared with normal adult retina. In total, we identified 899 proteins that were differentially expressed in retinoblastoma with a fold change of ≥2 of which 402 proteins were upregulated and 497 were down regulated. Insulin growth factor 2 mRNA binding protein 1 (IGF2BP1), chromogranin A, fetuin A (ASHG), Rac GTPase-activating protein 1 and midkine that were found to be overexpressed in retinoblastoma were further confirmed by immunohistochemistry by staining 15 independent retinoblastoma tissue sections. We further verified the effect of IGF2BP1 on cell proliferation and migration capability of a retinoblastoma cell line using knockdown studies.

Conclusions

In the present study mass spectrometry-based quantitative proteomic approach was applied to identify proteins differentially expressed in retinoblastoma tumor. This study identified the mitochondrial dysfunction and lipid metabolism pathways as the major pathways to be deregulated in retinoblastoma. Further knockdown studies of IGF2BP1 in retinoblastoma cell lines revealed it as a prospective therapeutic target for retinoblastoma.

Electronic supplementary material

The online version of this article (doi:10.1186/s12014-016-9128-7) contains supplementary material, which is available to authorized users.

Characterization of host response to Cryptococcus neoformans through quantitative proteomic analysis of cryptococcal meningitis co-infected with HIV

Cryptococcal meningitis is the most common opportunistic fungal infection causing morbidity and mortality (>60%) in HIV-associated immunocompromised individuals caused by Cryptococcus neoformans. Molecular mechanisms of cryptococcal infection in brain have been studied using experimental animal models and cell lines. There are limited studies for the molecular understanding of cryptococcal meningitis in human brain. The proteins involved in the process of invasion and infection in human brain still remains obscure. To this end we carried out mass spectrometry-based quantitative proteomics of frontal lobe brain tissues from cryptococcal meningitis patients and controls to identify host proteins that are associated with the pathogenesis of cryptococcal meningitis. We identified 317 proteins to be differentially expressed (≥2-fold) from a total of 3423 human proteins. We found proteins involved in immune response and signal transduction to be differentially expressed in response to cryptococcal infection in human brain. Immune response proteins including complement factors, major histocompatibility proteins, proteins previously known to be involved in fungal invasion to brain such as caveolin 1 and actin were identified to be differentially expressed in cryptococcal meningitis brain tissues co-infected with HIV. We also validated the expression status of 5 proteins using immunohistochemistry. Overexpression of major histocompatibility complexes, class I, B (HLA-B), actin alpha 2 smooth muscle aorta (ACTA2) and caveolin 1 (CAV1) and downregulation of peripheral myelin protein 2 (PMP2) and alpha crystallin B chain (CRYAB) in cryptococcal meningitis were confirmed by IHC-based validation experiments. This study provides the brain proteome profile of cryptococcal meningitis co-infected with HIV for a better understanding of the host response associated with the disease.

Proteogenomic Methods to Improve Genome Annotation

Annotation of protein coding genes in sequenced genomes has been routinely carried out using gene prediction programs guided by available transcript data. The advent of mass spectrometry has enabled the identification of proteins in a high-throughput manner. In addition to searching proteins annotated in public databases, mass spectrometry data can also be searched against conceptually translated genome as well as transcriptome to identify novel protein coding regions. This proteogenomics approach has resulted in the identification of novel protein coding regions in both prokaryotic and eukaryotic genomes. These studies have also revealed that some of the annotated noncoding RNAs and pseudogenes code for proteins. This approach is likely to become a part of most genome annotation workflows in the future. Here we describe a general methodology and approach that can be used for proteogenomics.

Comprehensive proteomics analysis of glycosomes from Leishmania donovani

Leishmania donovani is a kinetoplastid protozoan that causes a severe and fatal disease kala-azar, or visceral leishmaniasis. L. donovani infects human host after the phlebotomine sandfly takes a blood meal and resides within the phagolysosome of infected macrophages. Previous studies on host-parasite interactions have not focused on Leishmania organelles and the role that they play in the survival of this parasite within macrophages. Leishmania possess glycosomes that are unique and specialized subcellular microbody organelles. Glycosomes are known to harbor most peroxisomal enzymes and, in addition, they also possess nine glycolytic enzymes. In the present study, we have carried out proteomic profiling using high resolution mass spectrometry of a sucrose density gradient-enriched glycosomal fraction isolated from L. donovani promastigotes. This study resulted in the identification of 4022 unique peptides, leading to the identification of 1355 unique proteins from a preparation enriched in L. donovani glycosomes. Based on protein annotation, 566 (41.8%) were identified as hypothetical proteins with no known function. A majority of the identified proteins are involved in metabolic processes such as carbohydrate, lipid, and nucleic acid metabolism. Our present proteomic analysis is the most comprehensive study to date to map the proteome of L. donovani glycosomes.

PGTools: A Software Suite for Proteogenomic Data Analysis and Visualization

We describe PGTools, an open source software suite for analysis and visualization of proteogenomic data. PGTools comprises applications, libraries, customized databases, and visualization tools for analysis of mass-spectrometry data using combined proteomic and genomic backgrounds. A single command is sufficient to search databases, calculate false discovery rates, group and annotate proteins, generate peptide databases from RNA-Seq transcripts, identify altered proteins associated with cancer, and visualize genome scale peptide data sets using sophisticated visualization tools. We experimentally confirm a subset of proteogenomic peptides in human PANC-1 cells and demonstrate the utility of PGTools using a colorectal cancer data set that led to the identification of 203 novel protein coding regions missed by conventional proteomic approaches. PGTools should be equally useful for individual proteogenomic investigations as well as international initiatives such as chromosome-centric Human Proteome Project (C-HPP). PGTools is available at http://qcmg.org/bioinformatics/PGTools.

Host response profile of human brain proteome in toxoplasma encephalitis co-infected with HIV

Background

Toxoplasma encephalitis is caused by the opportunistic protozoan parasite Toxoplasma gondii. Primary infection with T. gondii in immunocompetent individuals remains largely asymptomatic. In contrast, in immunocompromised individuals, reactivation of the parasite results in severe complications and mortality. Molecular changes at the protein level in the host central nervous system and proteins associated with pathogenesis of toxoplasma encephalitis are largely unexplored. We used a global quantitative proteomic strategy to identify differentially regulated proteins and affected molecular networks in the human host during T. gondii infection with HIV co-infection.

Results

We identified 3,496 proteins out of which 607 proteins were differentially expressed (≥1.5-fold) when frontal lobe of the brain from patients diagnosed with toxoplasma encephalitis was compared to control brain tissues. We validated differential expression of 3 proteins through immunohistochemistry, which was confirmed to be consistent with mass spectrometry analysis. Pathway analysis of differentially expressed proteins indicated deregulation of several pathways involved in antigen processing, immune response, neuronal growth, neurotransmitter transport and energy metabolism.

Conclusions

Global quantitative proteomic approach adopted in this study generated a comparative proteome profile of brain tissues from toxoplasma encephalitis patients co-infected with HIV. Differentially expressed proteins include previously reported and several new proteins in the context of T. gondii and HIV infection, which can be further investigated. Molecular pathways identified to be associated with the disease should enhance our understanding of pathogenesis in toxoplasma encephalitis.

Electronic supplementary material

The online version of this article (doi:10.1186/1559-0275-11-39) contains supplementary material, which is available to authorized users.

Annotation of the zebrafish genome through an integrated transcriptomic and proteomic analysis

Accurate annotation of protein-coding genes is one of the primary tasks upon the completion of whole genome sequencing of any organism. In this study, we used an integrated transcriptomic and proteomic strategy to validate and improve the existing zebrafish genome annotation. We undertook high-resolution mass-spectrometry-based proteomic profiling of 10 adult organs, whole adult fish body, and two developmental stages of zebrafish (SAT line), in addition to transcriptomic profiling of six organs. More than 7,000 proteins were identified from proteomic analyses, and ∼ 69,000 high-confidence transcripts were assembled from the RNA sequencing data. Approximately 15% of the transcripts mapped to intergenic regions, the majority of which are likely long non-coding RNAs. These high-quality transcriptomic and proteomic data were used to manually reannotate the zebrafish genome. We report the identification of 157 novel protein-coding genes. In addition, our data led to modification of existing gene structures including novel exons, changes in exon coordinates, changes in frame of translation, translation in annotated UTRs, and joining of genes. Finally, we discovered four instances of genome assembly errors that were supported by both proteomic and transcriptomic data. Our study shows how an integrative analysis of the transcriptome and the proteome can extend our understanding of even well-annotated genomes.