A Cost-Effective High-Throughput Plasma and Serum Proteomics Workflow Enables Mapping of the Molecular Impact of Total Pancreatectomy with Islet Autotransplantation

Optimizing and integrating depletion and precipitation methods for plasma proteomics through data-independent acquisition-mass spectrometry

The application of plasma proteomics is a reliable approach for the discovery of biomarkers. However, the utilization of mass spectrometry-based proteomics in plasma encounters limitations due to the presence of high-abundant proteins (HAPs) and the vast dynamic range. To address this issue, we conducted an optimization and integration of depletion and precipitation strategies eliminating interference from HAPs. The optimized procedure involved utilizing 40 µL of beads for the removal of 1 µL of plasma, and maintaining a ratio of 1:1:1 between plasma, urea, and trichloroacetic acid for the precipitation of 50 µL of plasma. To facilitate high-throughput processing, experimental procedures were carried out utilizing 96-well plates. The depletion method identified a total of 1510 proteins, whereas the precipitated method yielded a total of 802 proteins. The integration of these methods yielded a total of 1794 proteins, including a wide concentration range spanning over 8 orders of magnitude. Furthermore, these approaches exhibited a commendable level of reproducibility, as indicated by median coefficients of variation of 14.7 % and 21.1 % for protein intensities, respectively. The integrative method was found to be effective in precisely quantifying yeast proteins that were intentionally spiked in plasma at predetermined rations of 5, 2, 0.5, and 0.2 with a high genuine positive recovery with a range of 71 % to 91 % of all yeast proteins. The use of a complementary and finely tuned approach involving depletion and precipitation demonstrates tremendous potential in the field of discovering protein biomarkers from large-scale cohort studies.

Early cellular and molecular signatures correlate with severity of West Nile virus infection

Infection with West Nile virus (WNV) drives a wide range of responses, from asymptomatic to flu-like symptoms/fever or severe cases of encephalitis and death. To identify cellular and molecular signatures distinguishing WNV severity, we employed systems profiling of peripheral blood from asymptomatic and severely ill individuals infected with WNV. We interrogated immune responses longitudinally from acute infection through convalescence employing single-cell protein and transcriptional profiling complemented with matched serum proteomics and metabolomics as well as multi-omics analysis. At the acute time point, we detected both elevation of pro-inflammatory markers in innate immune cell types and reduction of regulatory T cell activity in participants with severe infection, whereas asymptomatic donors had higher expression of genes associated with anti-inflammatory CD16+ monocytes. Therefore, we demonstrated the potential of systems immunology using multiple cell-type and cell-state-specific analyses to identify correlates of infection severity and host cellular activity contributing to an effective anti-viral response.

A clinical proteomics study of exhaled breath condensate and biomarkers for pulmonary embolism

Pulmonary embolism (PE) can be a diagnostic challenge. Current diagnostic markers for PE are unspecific and new diagnostic tools are needed. The air we exhale is a possible new source for biomarkers which can be tapped into by analysing the exhaled breath condensate (EBC). We analysed the EBC from patients with PE and controls to investigate if the EBC is a useful source for new diagnostic biomarkers of PE. We collected and analysed EBC samples from patients with suspected PE and controls matched on age and sex. Patients in whom PE was ruled out after diagnostic work-up were included in the control group to increase the sensitivity and generalizability of the identified markers. EBC samples were collected using an RTube™. The protein composition of the EBCs were analysed using data dependent label-free quantitative nano liquid chromatography-tandem mass spectrometry. EBC samples from 28 patients with confirmed PE, and 49 controls were analysed. A total of 928 EBC proteins were identified in the 77 EBC samples. As expected, a low protein concentration was determined which resulted in many proteins with unmeasurable levels in several samples. The levels of HSPA5, PEBP1 and SFTPA2 were higher and levels of POF1B, EPPK1, PSMA4, ALDOA, and CFL1 were lower in PE compared with controls. In conclusion, the human EBC contained a variety of endogenous proteins and may be a source for new diagnostic markers of PE and other diseases.

Advances in proteomics: characterization of the innate immune system after birth and during inflammation

Proteomics is the characterization of the protein composition, the proteome, of a biological sample. It involves the large-scale identification and quantification of proteins, peptides, and post-translational modifications. This review focuses on recent developments in mass spectrometry-based proteomics and provides an overview of available methods for sample preparation to study the innate immune system. Recent advancements in the proteomics workflows, including sample preparation, have significantly improved the sensitivity and proteome coverage of biological samples including the technically difficult blood plasma. Proteomics is often applied in immunology and has been used to characterize the levels of innate immune system components after perturbations such as birth or during chronic inflammatory diseases like rheumatoid arthritis (RA) and inflammatory bowel disease (IBD). In cancers, the tumor microenvironment may generate chronic inflammation and release cytokines to the circulation. In these situations, the innate immune system undergoes profound and long-lasting changes, the large-scale characterization of which may increase our biological understanding and help identify components with translational potential for guiding diagnosis and treatment decisions. With the ongoing technical development, proteomics will likely continue to provide increasing insights into complex biological processes and their implications for health and disease. Integrating proteomics with other omics data and utilizing multi-omics approaches have been demonstrated to give additional valuable insights into biological systems.

Choroid plexus-targeted NKCC1 overexpression to treat post-hemorrhagic hydrocephalus

Post-hemorrhagic hydrocephalus (PHH) refers to a life-threatening accumulation of cerebrospinal fluid (CSF) that occurs following intraventricular hemorrhage (IVH). An incomplete understanding of this variably progressive condition has hampered the development of new therapies beyond serial neurosurgical interventions. Here, we show a key role for the bidirectional Na-K-Cl cotransporter, NKCC1, in the choroid plexus (ChP) to mitigate PHH. Mimicking IVH with intraventricular blood led to increased CSF [K+] and triggered cytosolic calcium activity in ChP epithelial cells, which was followed by NKCC1 activation. ChP-targeted adeno-associated viral (AAV)-NKCC1 prevented blood-induced ventriculomegaly and led to persistently increased CSF clearance capacity. These data demonstrate that intraventricular blood triggered a trans-choroidal, NKCC1-dependent CSF clearance mechanism. Inactive, phosphodeficient AAV-NKCC1-NT51 failed to mitigate ventriculomegaly. Excessive CSF [K+] fluctuations correlated with permanent shunting outcome in humans following hemorrhagic stroke, suggesting targeted gene therapy as a potential treatment to mitigate intracranial fluid accumulation following hemorrhage.

Meta-analysis of published cerebrospinal fluid proteomics data identifies and validates metabolic enzyme panel as Alzheimer's disease biomarkers

To develop therapies for Alzheimer's disease, we need accurate in vivo diagnostics. Multiple proteomic studies mapping biomarker candidates in cerebrospinal fluid (CSF) resulted in little overlap. To overcome this shortcoming, we apply the rarely used concept of proteomics meta-analysis to identify an effective biomarker panel. We combine ten independent datasets for biomarker identification: seven datasets from 150 patients/controls for discovery, one dataset with 20 patients/controls for down-selection, and two datasets with 494 patients/controls for validation. The discovery results in 21 biomarker candidates and down-selection in three, to be validated in the two additional large-scale proteomics datasets with 228 diseased and 266 control samples. This resulting 3-protein biomarker panel differentiates Alzheimer's disease (AD) from controls in the two validation cohorts with areas under the receiver operating characteristic curve (AUROCs) of 0.83 and 0.87, respectively. This study highlights the value of systematically re-analyzing previously published proteomics data and the need for more stringent data deposition.

A Streamlined High-Throughput Plasma Proteomics Platform for Clinical Proteomics with Improved Proteome Coverage, Reproducibility, and Robustness

Mass spectrometry-based clinical proteomics requires high throughput, reproducibility, robustness, and comprehensive coverage to serve the needs of clinical diagnosis, prognosis, and personalized medicine. Oftentimes these requirements are contradictory to each other. We report the development of a streamlined High-Throughput Plasma Proteomics (sHTPP) platform for untargeted profiling of the blood plasma proteome, which includes 96-well plates and simplified procedures for sample preparation, disposable trap column for peptide loading, robust liquid chromatographic system for separation, data-independent acquisition in tandem mass spectrometry, and DIA-NN, FragPipe, and in-house peptide spectral library-based data analysis. Using the optimized platform at a throughput of 60 samples per day, over 600 protein groups including 57 FDA-approved biomarkers can be consistently identified from whole human plasma, and more than 85% of the detected proteins have 100% completeness in quantitative values across 300 samples. The balance achieved between proteome coverage, throughput, and reproducibility of this sHTPP platform makes it promising in clinical settings, where a large number of samples are to be measured quickly and reliably to support various needs of clinical medicine.

Mass spectrometry-based high-throughput proteomics and its role in biomedical studies and systems biology

There are multiple reasons why the next generation of biological and medical studies require increasing numbers of samples. Biological systems are dynamic, and the effect of a perturbation depends on the genetic background and environment. As a consequence, many conditions need to be considered to reach generalizable conclusions. Moreover, human population and clinical studies only reach sufficient statistical power if conducted at scale and with precise measurement methods. Finally, many proteins remain without sufficient functional annotations, because they have not been systematically studied under a broad range of conditions. In this review, we discuss the latest technical developments in mass spectrometry (MS)-based proteomics that facilitate large-scale studies by fast and efficient chromatography, fast scanning mass spectrometers, data-independent acquisition (DIA), and new software. We further highlight recent studies which demonstrate how high-throughput (HT) proteomics can be applied to capture biological diversity, to annotate gene functions or to generate predictive and prognostic models for human diseases.

Plasma proteome perturbation for CMV DNAemia in kidney transplantation

BACKGROUND

Cytomegalovirus (CMV) infection, either de novo or as reactivation after allotransplantation and chronic immunosuppression, is recognized to cause detrimental alloimmune effects, inclusive of higher susceptibility to graft rejection and substantive impact on chronic graft injury and reduced transplant survival. To obtain further insights into the evolution and pathogenesis of CMV infection in an immunocompromised host we evaluated changes in the circulating host proteome serially, before and after transplantation, and during and after CMV DNA replication (DNAemia), as measured by quantitative polymerase chain reaction (QPCR).

METHODS

LC-MS-based proteomics was conducted on 168 serially banked plasma samples, from 62 propensity score-matched kidney transplant recipients. Patients were stratified by CMV replication status into 31 with CMV DNAemia and 31 without CMV DNAemia. Patients had blood samples drawn at protocol times of 3- and 12-months post-transplant. Additionally, blood samples were also drawn before and 1 week and 1 month after detection of CMV DNAemia. Plasma proteins were analyzed using an LCMS 8060 triple quadrupole mass spectrometer. Further, public transcriptomic data on time matched PBMCs samples from the same patients was utilized to evaluate integrative pathways. Data analysis was conducted using R and Limma.

RESULTS

Samples were segregated based on their proteomic profiles with respect to their CMV Dnaemia status. A subset of 17 plasma proteins was observed to predict the onset of CMV at 3 months post-transplant enriching platelet degranulation (FDR, 4.83E-06), acute inflammatory response (FDR, 0.0018), blood coagulation (FDR, 0.0018) pathways. An increase in many immune complex proteins were observed at CMV infection. Prior to DNAemia the plasma proteome showed changes in the anti-inflammatory adipokine vaspin (SERPINA12), copper binding protein ceruloplasmin (CP), complement activation (FDR = 0.03), and proteins enriched in the humoral (FDR = 0.01) and innate immune responses (FDR = 0.01).

CONCLUSION

Plasma proteomic and transcriptional perturbations impacting humoral and innate immune pathways are observed during CMV infection and provide biomarkers for CMV disease prediction and resolution. Further studies to understand the clinical impact of these pathways can help in the formulation of different types and duration of anti-viral therapies for the management of CMV infection in the immunocompromised host.

Longitudinal serum proteomics analyses identify unique and overlapping host response pathways in Lyme disease and West Nile virus infection

Advancement in proteomics methods for interrogating biological samples has helped identify disease biomarkers for early diagnostics and unravel underlying molecular mechanisms of disease. Herein, we examined the serum proteomes of 23 study participants presenting with one of two common arthropod-borne infections: Lyme disease (LD), an extracellular bacterial infection or West Nile virus infection (WNV), an intracellular viral infection. The LC/MS based serum proteomes of samples collected at the time of diagnosis and during convalescence were assessed using a depletion-based high-throughput shotgun proteomics (dHSP) pipeline as well as a non-depleting blotting-based low-throughput platform (MStern). The LC/MS integrated analyses identified host proteome responses in the acute and recovery phases shared by LD and WNV infections, as well as differentially abundant proteins that were unique to each infection. Notably, we also detected proteins that distinguished localized from disseminated LD and asymptomatic from symptomatic WNV infection. The proteins detected in both diseases with the dHSP pipeline identified unique and overlapping proteins detected with the non-depleting MStern platform, supporting the utility of both detection methods. Machine learning confirmed the use of the serum proteome to distinguish the infection from healthy control sera but could not develop discriminatory models between LD and WNV at current sample numbers. Our study is the first to compare the serum proteomes in two arthropod-borne infections and highlights the similarities in host responses even though the pathogens and the vectors themselves are different.

Using plasma proteomics to investigate viral infections of the central nervous system including patients with HIV-associated neurocognitive disorders

State-of-the-art liquid chromatography/mass spectrometry (LC/MS)-based proteomic technologies, using microliter amounts of patient plasma, can detect and quantify several hundred plasma proteins in a high throughput fashion, allowing for the discovery of clinically relevant protein biomarkers and insights into the underlying pathobiological processes. Using such an in-house developed high throughput plasma proteomics allowed us to identify and quantify > 400 plasmas proteins in 15 min per sample, i.e., a throughput of 100 samples/day. We demonstrated the clinical applicability of our method in this pilot study by mapping the plasma proteomes from patients infected with human immunodeficiency virus (HIV) or herpes virus, both groups with involvement of the central nervous system (CNS). We found significant disease-specific differences in the plasma proteomes. The most notable difference was a decrease in the levels of several coagulation-associated proteins in HIV vs. herpes virus, among other dysregulated biological pathways providing insight into the differential pathophysiology of HIV compared to herpes virus infection. In a subsequent analysis, we found several plasma proteins associated with immunity and metabolism to differentiate patients with HIV-associated neurocognitive disorders (HAND) compared to cognitively normal people with HIV (PWH), suggesting the presence of plasma-based biomarkers to distinguishing HAND from cognitively normal PWH. Overall, our high-throughput plasma proteomics pipeline enables the identification of distinct proteomic signatures of HIV and herpes virus, which may help illuminate divergent pathophysiology behind virus-associated neurological disorders.

Selenium Nanoparticles (SeNPs) Immunomodulation Is More Than Redox Improvement: Serum Proteomics and Transcriptomic Analyses

Selenium nanoparticles (SeNPs) are a novel elemental form selenium and often reported to possess beneficial bioactivities such as anticancer, promoting bone growth and immunomodulation. Our previous study demonstrated that chitosan-stabilized SeNPs have strong activity in immunomodulation. However, the mechanism underlying the immunomodulation of SeNPs is still unknown. The aim of this study is to identify the molecular mechanisms involved in SeNP-induced immunomodulation. Using zebrafish, as a common immunological animal model with a highly conserved molecular mechanism with other vertebrates, we conducted serum proteomic and tissue transcriptome analyses on individuals fed with SeNP in healthy or disease conditions. We also compared differences between SeNPs and an exogenous antioxidant Trolox in immune activity and redox regulation. Our results suggest that the immunomodulation activity was highly related to antioxidant activity and lipid metabolism. Interestingly, the biological functions enhanced by SeNP were almost identical in the healthy and disease conditions. However, while the SeNP was suppressing ROS in healthy individuals, it promoted ROS formation during disease condition. This might be related to the defense mechanism against pathogens. SOD and NFkβ appeared to be the key molecular switch changing effect of SeNPs when individuals undergo infection, indicating the close relationship between immune and redox regulation.

Urine Proteomics Reveals Sex-Specific Response to Total Pancreatectomy With Islet Autotransplantation

OBJECTIVES

Total pancreatectomy with islet autotransplantation (TPIAT) is a surgical option for refractory chronic pancreatitis-related pain. Despite the known clinical implications of TPIAT, the molecular effects remain poorly investigated. We performed the first hypothesis-generating study of the urinary proteome before and after TPIAT.

METHODS

Twenty-two patients eligible for TPIAT were prospectively enrolled. Urine samples were collected the week before and 12 to 18 months after TPIAT. The urine samples were prepared for bottom-up label-free quantitative proteomics using the "MStern" protocol.

RESULTS

Using 17 paired samples, we identified 2477 urinary proteins, of which 301 were significantly changed post-TPIAT versus pre-TPIAT. Our quantitative analysis revealed that the molecular response to TPIAT was highly sex-specific, with pronounced sex differences pre-TPIAT but minimal differences afterward. Comparing post-TPIAT versus pre-TPIAT, we found changes in cell-cell adhesion, intracellular vacuoles, and immune response proteins. After surgery, immunoglobulins, complement proteins, and cathepsins were increased, findings that may reflect glomerular damage. Finally, we identified both known and novel markers for immunoglobulin A nephropathy after 1 patient developed the disease 2 years after TPIAT.

CONCLUSIONS

We found distinct changes in the urinary proteomic profile after TPIAT and the response to TPIAT is highly sex-specific.

Plasma Proteomic Analysis Distinguishes Severity Outcomes of Human Ebola Virus Disease

Ebola virus (EBV) disease (EVD) is a highly virulent systemic disease characterized by an aggressive systemic inflammatory response and impaired vascular and coagulation systems, often leading to uncontrolled hemorrhaging and death. In this study, the proteomes of 38 sequential plasma samples from 12 confirmed EVD patients were analyzed. Of these 12 cases, 9 patients received treatment with interferon beta 1a (IFN-β-1a), 8 survived EVD, and 4 died; 2 of these 4 fatalities had received IFN-β-1a. Our analytical strategy combined three platforms targeting different plasma subproteomes: a liquid chromatography-mass spectrometry (LC-MS)-based analysis of the classical plasma proteome, a protocol that combines the depletion of abundant plasma proteins and LC-MS to detect less abundant plasma proteins, and an antibody-based cytokine/chemokine multiplex assay. These complementary platforms provided comprehensive data on 1,000 host and viral proteins. Examination of the early plasma proteomes revealed protein signatures that differentiated between fatalities and survivors. Moreover, IFN-β-1a treatment was associated with a distinct protein signature. Next, we examined those proteins whose abundances reflected viral load measurements and the disease course: resolution or progression. Our data identified a prognostic 4-protein biomarker panel (histone H1-5, moesin, kininogen 1, and ribosomal protein L35 [RPL35]) that predicted EVD outcomes more accurately than the onset viral load. IMPORTANCE As evidenced by the 2013-2016 outbreak in West Africa, Ebola virus (EBV) disease (EVD) poses a major global health threat. In this study, we characterized the plasma proteomes of 12 individuals infected with EBV, using two different LC-MS-based proteomics platforms and an antibody-based multiplexed cytokine/chemokine assay. Clear differences were observed in the host proteome between individuals who survived and those who died, at both early and late stages of the disease. From our analysis, we derived a 4-protein prognostic biomarker panel that may help direct care. Given the ease of implementation, a panel of these 4 proteins or subsets thereof has the potential to be widely applied in an emergency setting in resource-limited regions.

Determinants of B-Cell Compartment Hyperactivation in European Adolescents Living With Perinatally Acquired HIV-1 After Over 10 Years of Suppressive Therapy

Background

Despite a successful antiretroviral therapy (ART), adolescents living with perinatally acquired HIV (PHIV) experience signs of B-cell hyperactivation with expansion of 'namely' atypical B-cell phenotypes, including double negative (CD27-IgD-) and termed age associated (ABCs) B-cells (T-bet+CD11c+), which may result in reduced cell functionality, including loss of vaccine-induced immunological memory and higher risk of developing B-cells associated tumors. In this context, perinatally HIV infected children (PHIV) deserve particular attention, given their life-long exposure to chronic immune activation.

Methods

We studied 40 PHIV who started treatment by the 2nd year of life and maintained virological suppression for 13.5 years, with 5/40 patients experiencing transient elevation of the HIV-1 load in the plasma (Spike). We applied a multi-disciplinary approach including immunological B and T cell phenotype, plasma proteomics analysis, and serum level of anti-measles antibodies as functional correlates of vaccine-induced immunity.

Results

Phenotypic signs of B cell hyperactivation were elevated in subjects starting ART later (%DN T-bet+CD11c+ p=0.03; %AM T-bet+CD11c+ p=0.02) and were associated with detectable cell-associated HIV-1 RNA (%AM T-bet+CD11c+ p=0.0003) and transient elevation of the plasma viral load (spike). Furthermore, B-cell hyperactivation appeared to be present in individuals with higher frequency of exhausted T-cells, in particular: %CD4 TIGIT+ were associated with %DN (p=0.008), %DN T-bet+CD11c+ (p=0.0002) and %AM T-bet+CD11c+ (p=0.002) and %CD4 PD-1 were associated with %DN (p=0.048), %DN T-bet+CD11c+ (p=0.039) and %AM T-bet+CD11c+ (p=0.006). The proteomic analysis revealed that subjects with expansion of these atypical B-cells and exhausted T-cells had enrichment of proteins involved in immune inflammation and complement activation pathways. Furthermore, we observed that higher levels of ABCs were associated a reduced capacity to maintain vaccine-induced antibody immunity against measles (%B-cells CD19+CD10- T-bet+, p=0.035).

Conclusion

We identified that the levels of hyperactivated B cell subsets were strongly affected by time of ART start and associated with clinical, viral, cellular and plasma soluble markers. Furthermore, the expansion of ABCs also had a direct impact on the capacity to develop antibodies response following routine vaccination.

RapiGest precipitation depends on peptide concentration

The mass spectrometry-compatible surfactant RapiGest promotes the enzymatic digestion of proteins by facilitating their unfolding while retaining enzymatic activity. RapiGest consists of a hydrophilic head and a hydrophobic tail, which can be separated by acid hydrolysis. This allows for removal of RapiGest prior to mass spectrometric analysis via precipitation and solid phase extraction. During in-solution digestion experiments with RapiGest, we noticed a high variability in the formation of precipitates after acid hydrolysis, implying that RapiGest precipitation is sample-dependent. We show that RapiGest hydrolyses efficiently under acidic conditions and that differences in precipitation are solely due to protein/peptide concentration. Furthermore, we demonstrate that RapiGest precipitation can be triggered by the addition of intact proteins, providing a strategy for its efficient removal from highly diluted samples. Data are available via ProteomeXchange with identifier PXD025982.

Immunophenotyping assessment in a COVID-19 cohort (IMPACC): A prospective longitudinal study

The Immunophenotyping Assessment in a COVID-19 Cohort (IMPACC) is a prospective longitudinal study designed to enroll 1000 hospitalized patients with COVID-19 (NCT04378777). IMPACC collects detailed clinical, laboratory, and radiographic data along with longitudinal biologic sampling of blood and respiratory secretions for in-depth testing. Clinical and laboratory data are integrated to identify immunologic, virologic, proteomic, metabolomic, and genomic features of COVID-19–related susceptibility, severity, and disease progression. The goals of IMPACC are to better understand the contributions of pathogen dynamics and host immune responses to the severity and course of COVID-19 and to generate hypotheses for identification of biomarkers and effective therapeutics, including optimal timing of such interventions. In this report, we summarize the IMPACC study design and protocols including clinical criteria and recruitment, multisite standardized sample collection and processing, virologic and immunologic assays, harmonization of assay protocols, high-level analyses, and the data sharing plans.

Ultra-fast proteomics with Scanning SWATH

Accurate quantification of the proteome remains challenging for large sample series and longitudinal experiments. We report a data-independent acquisition method, Scanning SWATH, that accelerates mass spectrometric (MS) duty cycles, yielding quantitative proteomes in combination with short gradients and high-flow (800 µl min-1) chromatography. Exploiting a continuous movement of the precursor isolation window to assign precursor masses to tandem mass spectrometry (MS/MS) fragment traces, Scanning SWATH increases precursor identifications by ~70% compared to conventional data-independent acquisition (DIA) methods on 0.5-5-min chromatographic gradients. We demonstrate the application of ultra-fast proteomics in drug mode-of-action screening and plasma proteomics. Scanning SWATH proteomes capture the mode of action of fungistatic azoles and statins. Moreover, we confirm 43 and identify 11 new plasma proteome biomarkers of COVID-19 severity, advancing patient classification and biomarker discovery. Thus, our results demonstrate a substantial acceleration and increased depth in fast proteomic experiments that facilitate proteomic drug screens and clinical studies.

Sample Preparation for High-Throughput Urine Proteomics Using 96-Well Polyvinylidene Fluoride (PVDF) Membranes

Proteomics analysis of urine samples allows for studying the impact of system perturbation. However, meaningful proteomics-based biomarker discovery projects often require the analysis of large patient cohorts with hundreds of samples to describe the biological variability. Thus, robust high-throughput sample processing methods are a prerequisite for clinical proteomics pipelines that minimize experimental bias due to individual sample processing methods. Herein we describe a high-throughput method for parallel 96-well plate-based processing of urine samples for subsequent LC/MS-based proteomic analyses. Protein digestion and subsequent sample processing steps are efficiently performed in 96-well polyvinylidene fluoride (PVDF) membrane plate allowing for the use of vacuum manifolds for rapid liquid transfer, and multichannel pipettes and/or liquid handing robots. In this chapter we make available a detailed step-by-step protocol for our 'MStern blotting' sample processing strategy applied to patient urine samples followed by mass spectrometry-based proteomics analysis. Subsequently, we provide an example application using minimal volume of urine samples (e.g. 150 μL) collected from children pre and post thoracotomy to identify the predominant sites of protein catabolism and aid in the design of therapies to ameliorate protein catabolism and breakdown during critical illness. Furthermore, we demonstrate how the systemic state is reflected in the urine as an easily obtainable, stable, and safe biofluid.

High-throughput, in-depth and estimated absolute quantification of plasma proteome using data-independent acquisition/mass spectrometry ("HIAP-DIA")

Mass spectrometry-based plasma proteomics has been demonstrated to be a useful tool capable of quantifying hundreds of proteins in a single LC-MS/MS experiment, for biomarker discovery or elucidation of disease mechanisms. We developed a novel data-independent acquisition (DIA)/MS-based workflow for high-throughput, in-depth and estimated absolute quantification of plasma proteins (termed HIAP-DIA), without depleting high-abundant proteins, in a single-shot experiment. In HIAP-DIA workflow, we generated an ultra-deep cumulative undepleted and depleted spectral library which contained 55,157 peptides and 5,328 proteins, optimized column length (50 cm) and gradient (90 min) of liquid chromatography instrumentation, optimized 50 DIA segments with average isolation window 17 Th, and selected reference proteins for estimated absolute quantification of all plasma proteins. A total of 606 proteins were quantified in triplicate, and 427 proteins were quantified with CV <20% in plasma proteome. R-squared value of overlapped 208 endogenous PQ500 estimated protein amounts from HIAP-DIA and absolute quantification with internal standards was 0.82, indicating high quantification accuracy of HIAP-DIA. As a pilot study, the HIAP-DIA approach described here was applied to a myelodysplastic syndromes (MDS) disease cohort. We achieved absolute quantification of 789 plasma proteins in 22 clinical plasma samples, spanning less than six orders of magnitude with quantification limit 10-20 ng/mL, and discovered 95 differentially expressed proteins providing insights into MDS pathophysiology.

Analysis of complement deposition and processing on Chlamydia trachomatis

Chlamydia trachomatis (C. trachomatis) is the leading cause of sexually transmitted bacterial infections worldwide, with over 120 million annual cases. C. trachomatis infections are associated with severe reproductive complications in women such as extrauterine pregnancy and tubal infertility. The infections are often long lasting, associated with immunopathology, and fail to elicit protective immunity which makes recurrent infections common. The immunological mechanisms involved in C. trachomatis infections are only partially understood. Murine infection models suggest that the complement system plays a significant role in both protective immunity and immunopathology during primary Chlamydia infections. However, only limited structural and mechanistic evidence exists on complement-mediated immunity against C. trachomatis. To expand our current knowledge on this topic, we analyzed global complement deposition on C. trachomatis using comprehensive in-depth mass spectrometry-based proteomics. We show that factor B, properdin, and C4b bind to C. trachomatis demonstrating that C. trachomatis-induced complement activation proceeds through at least two activation pathways. Complement activation leads to cleavage and deposition of C3 and C5 activation products, causing initiation of the terminal complement pathway and deposition of C5b, C6, C7, C8, C9 on C. trachomatis. Interestingly, using immunoelectron microscopy, we show that C5b-9 deposition occurred sporadically and only in rare cases formed complete lytic terminal complexes, possibly caused by the presence of the negative regulators vitronectin and clusterin. Finally, cleavage analysis of C3 demonstrated that deposited C3b is degraded to the opsonins iC3b and C3dg and that this complement opsonization facilitates C. trachomatis binding to human B-cells.

Preparing for Life: Plasma Proteome Changes and Immune System Development During the First Week of Human Life

Neonates have heightened susceptibility to infections. The biological mechanisms are incompletely understood but thought to be related to age-specific adaptations in immunity due to resource constraints during immune system development and growth. We present here an extended analysis of our proteomics study of peripheral blood-plasma from a study of healthy full-term newborns delivered vaginally, collected at the day of birth and on day of life (DOL) 1, 3, or 7, to cover the first week of life. The plasma proteome was characterized by LC-MS using our established 96-well plate format plasma proteomics platform. We found increasing acute phase proteins and a reduction of respective inhibitors on DOL1. Focusing on the complement system, we found increased plasma concentrations of all major components of the classical complement pathway and the membrane attack complex (MAC) from birth onward, except C7 which seems to have near adult levels at birth. In contrast, components of the lectin and alternative complement pathways mainly decreased. A comparison to whole blood messenger RNA (mRNA) levels enabled characterization of mRNA and protein levels in parallel, and for 23 of the 30 monitored complement proteins, the whole blood transcript information by itself was not reflective of the plasma protein levels or dynamics during the first week of life. Analysis of immunoglobulin (Ig) mRNA and protein levels revealed that IgM levels and synthesis increased, while the plasma concentrations of maternally transferred IgG1-4 decreased in accordance with their in vivo half-lives. The neonatal plasma ratio of IgG1 to IgG2-4 was increased compared to adult values, demonstrating a highly efficient IgG1 transplacental transfer process. Partial compensation for maternal IgG degradation was achieved by endogenous synthesis of the IgG1 subtype which increased with DOL. The findings were validated in a geographically distinct cohort, demonstrating a consistent developmental trajectory of the newborn's immune system over the first week of human life across continents. Our findings indicate that the classical complement pathway is central for newborn immunity and our approach to characterize the plasma proteome in parallel with the transcriptome will provide crucial insight in immune ontogeny and inform new approaches to prevent and treat diseases.

Towards Precision Vaccines: Lessons From the Second International Precision Vaccines Conference

Other than clean drinking water, vaccines have been the most effective public health intervention in human history, yet their full potential is still untapped. To date, vaccine development has been largely limited to empirical approaches focused on infectious diseases and has targeted entire populations, potentially disregarding distinct immunity in vulnerable populations such as infants, elders, and the immunocompromised. Over the past few decades innovations in genetic engineering, adjuvant discovery, formulation science, and systems biology have fueled rapid advances in vaccine research poised to consider demographic factors (e.g., age, sex, genetics, and epigenetics) in vaccine discovery and development. Current efforts are focused on leveraging novel approaches to vaccine discovery and development to optimize vaccinal antigen and, as needed, adjuvant systems to enhance vaccine immunogenicity while maintaining safety. These approaches are ushering in an era of precision vaccinology aimed at tailoring immunization for vulnerable populations with distinct immunity. To foster collaboration among leading vaccinologists, government, policy makers, industry partners, and funders from around the world, the Precision Vaccines Program at Boston Children's Hospital hosted the 2nd International Precision Vaccines Conference (IPVC) at Harvard Medical School on the 17th-18th October 2019. The conference convened experts in vaccinology, including vaccine formulation and adjuvantation, immunology, cell signaling, systems biology, biostatistics, bioinformatics, as well as vaccines for non-infectious indications such as cancer and opioid use disorder. Herein we review highlights from the 2nd IPVC and discuss key concepts in the field of precision vaccines.

Ultra-High-Throughput Clinical Proteomics Reveals Classifiers of COVID-19 Infection

The COVID-19 pandemic is an unprecedented global challenge, and point-of-care diagnostic classifiers are urgently required. Here, we present a platform for ultra-high-throughput serum and plasma proteomics that builds on ISO13485 standardization to facilitate simple implementation in regulated clinical laboratories. Our low-cost workflow handles up to 180 samples per day, enables high precision quantification, and reduces batch effects for large-scale and longitudinal studies. We use our platform on samples collected from a cohort of early hospitalized cases of the SARS-CoV-2 pandemic and identify 27 potential biomarkers that are differentially expressed depending on the WHO severity grade of COVID-19. They include complement factors, the coagulation system, inflammation modulators, and pro-inflammatory factors upstream and downstream of interleukin 6. All protocols and software for implementing our approach are freely available. In total, this work supports the development of routine proteomic assays to aid clinical decision making and generate hypotheses about potential COVID-19 therapeutic targets.

Serum proteome changes and accelerated reduction of fat mass after laparoscopic gastric plication in morbidly obese patients

Laparoscopic Gastric Plication (LGP) is a relatively new bariatric surgical procedure which no part of the stomach is removed. It is not clearly understood how LGP leads to fatty tissue reduction. We aimed to investigate the impact of LGP on serum proteome and understand molecular mechanisms of LGP-induced weight loss post-surgery. A Prospective observational study of 16 obese individuals who underwent LGP was performed. A Label-free quantitative shotgun proteomics approach was used to compare serum proteome of subjects before surgery with serum of the same individuals 1 to 2 months post-surgery (T1) and 4 to 5 months post-surgery (T2). The proteome analysis revealed that 48 proteins were differentially regulated between pre-surgery and T1, and seven proteins between pre-surgery and T2 of which six proteins were shared between the two timepoints. Among differentially regulated proteins, four proteins (SRGN, FETUB, LCP1 and CFP) have not previously been described in the context of BMI/weight loss. Despite few differences following LGP, most regulated serum proteins are in accordance with alternative weight loss procedures. Pathway analysis revealed changes to lipid- and inflammatory pathways, including PPARα/RXRα, LXR/RXR and FXR/RXR activation, especially at T1. At T2, the pathways related to inflammation and immune system are most affected. SIGNIFICANCE: Among the available clinical therapies for morbid obesity, bariatric surgery is considered as the most effective approach to achieve long-term weight loss, alongside a significant improvement in metabolic syndrome. However, very little is known about the underlying mechanism associated with significant weight loss post-surgery. Understanding such mechanisms could lead to development of safer non-surgical weight loss approaches. We here present the first analysis of the impact of LGP on the serum proteome, to bring new insights into the underlying molecular mechanism. Our findings indicate that LGP has a comprehensive systemic effect based on the blood serum proteome profile which might account for accelerated reduction of fat mass after surgery, thus, food restriction is not the only reason for weight loss following this unique surgical approach. As secretory regions of the stomach are preserved in LGP and it is associated with minimal physiological and anatomical changes, the findings are of high importance in the field of bariatric surgery and weight loss.

OMIC Technologies and Vaccine Development: From the Identification of Vulnerable Individuals to the Formulation of Invulnerable Vaccines

Routine vaccination is among the most effective clinical interventions to prevent diseases as it is estimated to save over 3 million lives every year. However, the full potential of global immunization programs is not realised because population coverage is still suboptimal. This is also due to the inadequate immune response and paucity of informative correlates of protection upon immunization of vulnerable individuals such as newborns, preterm infants, pregnant women, and elderly individuals as well as those patients affected by chronic and immune compromising medical conditions. In addition, these groups are undervaccinated for a number of reasons, including lack of awareness of vaccine-preventable diseases and uncertainty or misconceptions about the safety and efficacy of vaccination by parents and healthcare providers. The presence of these nonresponders/undervaccinated individuals represents a major health and economic burden to society, which will become particularly difficult to address in settings with limited public resources. This review describes innovative and experimental approaches that can help identify specific genomic profiles defining nonresponder individuals for whom specific interventions might be needed. We will provide examples that show how such information can be useful to identify novel biomarkers of safety and immunogenicity for future vaccine trials. Finally, we will discuss how system biology “OMICs” data can be used to design bioinformatic tools to predict the vaccination outcome providing genetic and molecular “signatures” of protective immune response. This strategy may soon enable identification of signatures highly predictive of vaccine safety, immunogenicity, and efficacy/protection thereby informing personalized vaccine interventions in vulnerable populations.

Dynamic molecular changes during the first week of human life follow a robust developmental trajectory

Systems biology can unravel complex biology but has not been extensively applied to human newborns, a group highly vulnerable to a wide range of diseases. We optimized methods to extract transcriptomic, proteomic, metabolomic, cytokine/chemokine, and single cell immune phenotyping data from <1 ml of blood, a volume readily obtained from newborns. Indexing to baseline and applying innovative integrative computational methods reveals dramatic changes along a remarkably stable developmental trajectory over the first week of life. This is most evident in changes of interferon and complement pathways, as well as neutrophil-associated signaling. Validated across two independent cohorts of newborns from West Africa and Australasia, a robust and common trajectory emerges, suggesting a purposeful rather than random developmental path. Systems biology and innovative data integration can provide fresh insights into the molecular ontogeny of the first week of life, a dynamic developmental phase that is key for health and disease.

The first week of life impacts health for all of life, but the mechanisms are little-understood. Here the authors extract multi-omic data from small volumes of blood to study the dynamic molecular changes during the first week of life, revealing a robust developmental trajectory common to different populations.

Microvesicle Proteomic Profiling of Uterine Liquid Biopsy for Ovarian Cancer Early Detection

High-grade ovarian cancer (HGOC) is the leading cause of mortality from gynecological malignancies, because of diagnosis at a metastatic stage. Current screening options fail to improve mortality because of the absence of early-stage-specific biomarkers. We postulated that a liquid biopsy, such as utero-tubal lavage (UtL), may identify localized lesions better than systemic approaches of serum/plasma analysis. Further, while mutation-based assays are challenged by the rarity of tumor DNA within nonmutated DNA, analyzing the proteomic profile, is expected to enable earlier detection, as it reveals perturbations in both the tumor as well as in its microenvironment. To attain deep proteomic coverage and overcome the high dynamic range of this body fluid, we applied our method for microvesicle proteomics to the UtL samples. Liquid biopsies from HGOC patients (n = 49) and controls (n = 127) were divided into a discovery and validation sets. Data-dependent analysis of the samples on the Q-Exactive mass spectrometer provided depth of 8578 UtL proteins in total, and on average ∼3000 proteins per sample. We used support vector machine algorithms for sample classification, and crossed three feature-selection algorithms, to construct and validate a 9-protein classifier with 70% sensitivity and 76.2% specificity. The signature correctly identified all Stage I lesions. These results demonstrate the potential power of microvesicle-based proteomic biomarkers for early cancer diagnosis.

PROspective Evaluation of Chronic Pancreatitis for EpidEmiologic and Translational StuDies: Rationale and Study Design for PROCEED From the Consortium for the Study of Chronic Pancreatitis, Diabetes, and Pancreatic Cancer

Prospective Evaluation of Chronic Pancreatitis for Epidemiologic and Translational Studies (PROCEED) is the first prospective, observational cohort study of chronic pancreatitis (CP) in the United States. The primary goals of PROCEED are to define disease progression, test the predictive capability of candidate biomarkers, and develop a platform to conduct translational and mechanistic studies in CP. Using objective and consensus-driven criteria, PROCEED will enroll adults at different stages of CP-controls, suspected CP, and definite CP. In addition to collecting detailed information using structured case report forms and protocol-mandated evaluations at baseline and during follow-up, PROCEED will establish a linked biorepository of blood, urine, saliva, stool, pancreatic fluid, and pancreatic tissue. Enrollment for PROCEED began in June 2017. As of July 1, 2018, nine clinical centers of the Consortium for the Study of Chronic Pancreatitis, Diabetes, and Pancreatic Cancer are enrolling, and 350 subjects have completed baseline evaluation. In conclusion, PROCEED will provide the most accurate and reliable estimates to date on progression of CP. The established cohort and biorepository will facilitate numerous analyses, leading to new strategies for diagnosis, methods to monitor disease progression, and treatment of CP.