A proximity proteomics pipeline with improved reproducibility and throughput.

Proximity labeling (PL) via biotinylation coupled with mass spectrometry (MS) captures spatial proteomes in cells. Large-scale processing requires a workflow minimizing hands-on time and enhancing quantitative reproducibility. We introduced a scalable PL pipeline integrating automated enrichment of biotinylated proteins in a 96-well plate format. Combining this with optimized quantitative MS based on data-independent acquisition (DIA), we increased sample throughput and improved protein identification and quantification reproducibility. We applied this pipeline to delineate subcellular proteomes across various compartments. Using the 5HT2A serotonin receptor as a model, we studied temporal changes of proximal interaction networks induced by receptor activation. In addition, we modified the pipeline for reduced sample input to accommodate CRISPR-based gene knockout, assessing dynamics of the 5HT2A network in response to perturbation of selected interactors. This PL approach is universally applicable to PL proteomics using biotinylation-based PL enzymes, enhancing throughput and reproducibility of standard protocols

CRL4^(AMBRA1) targets Elongin C for ubiquitination and degradation to modulate CRL5 signaling

Multi‐subunit cullin‐RING ligases (CRLs) are the largest family of ubiquitin E3 ligases in humans. CRL activity is tightly regulated to prevent unintended substrate degradation or autocatalytic degradation of CRL subunits. Using a proteomics strategy, we discovered that CRL4^(AMBRA1) (CRL substrate receptor denoted in superscript) targets Elongin C (ELOC), the essential adapter protein of CRL5 complexes, for polyubiquitination and degradation. We showed that the ubiquitin ligase function of CRL4^(AMBRA1) is required to disrupt the assembly and attenuate the ligase activity of human CRL5^(SOCS3) and HIV‐1 CRL5^(VIF) complexes as AMBRA1 depletion leads to hyperactivation of both CRL5 complexes. Moreover, CRL4^(AMBRA1) modulates interleukin‐6/STAT3 signaling and HIV‐1 infectivity that are regulated by CRL5^(SOCS3) and CRL5^(VIF), respectively. Thus, by discovering a substrate of CRL4^(AMBRA1), ELOC, the shared adapter of CRL5 ubiquitin ligases, we uncovered a novel CRL cross‐regulation pathway

CRL4^(AMBRA1) targets Elongin C for ubiquitination and degradation to modulate CRL5 signaling

Multi‐subunit cullin‐RING ligases (CRLs) are the largest family of ubiquitin E3 ligases in humans. CRL activity is tightly regulated to prevent unintended substrate degradation or autocatalytic degradation of CRL subunits. Using a proteomics strategy, we discovered that CRL4^(AMBRA1) (CRL substrate receptor denoted in superscript) targets Elongin C (ELOC), the essential adapter protein of CRL5 complexes, for polyubiquitination and degradation. We showed that the ubiquitin ligase function of CRL4^(AMBRA1) is required to disrupt the assembly and attenuate the ligase activity of human CRL5^(SOCS3) and HIV‐1 CRL5^(VIF) complexes as AMBRA1 depletion leads to hyperactivation of both CRL5 complexes. Moreover, CRL4^(AMBRA1) modulates interleukin‐6/STAT3 signaling and HIV‐1 infectivity that are regulated by CRL5^(SOCS3) and CRL5^(VIF), respectively. Thus, by discovering a substrate of CRL4^(AMBRA1), ELOC, the shared adapter of CRL5 ubiquitin ligases, we uncovered a novel CRL cross‐regulation pathway

SARS-CoV-2 variants evolve convergent strategies to remodel the host response

SARS-CoV-2 variants of concern (VOCs) emerged during the COVID-19 pandemic. Here, we used unbiased systems approaches to study the host-selective forces driving VOC evolution. We discovered that VOCs evolved convergent strategies to remodel the host by modulating viral RNA and protein levels, altering viral and host protein phosphorylation, and rewiring virus-host protein-protein interactions. Integrative computational analyses revealed that although Alpha, Beta, Gamma, and Delta ultimately converged to suppress interferon-stimulated genes (ISGs), Omicron BA.1 did not. ISG suppression correlated with the expression of viral innate immune antagonist proteins, including Orf6, N, and Orf9b, which we mapped to specific mutations. Later Omicron subvariants BA.4 and BA.5 more potently suppressed innate immunity than early subvariant BA.1, which correlated with Orf6 levels, although muted in BA.4 by a mutation that disrupts the Orf6-nuclear pore interaction. Our findings suggest that SARS-CoV-2 convergent evolution overcame human adaptive and innate immune barriers, laying the groundwork to tackle future pandemics

A combined top-down and bottom-up MS approach for the characterization of hemoglobin variants in Rhesus monkeys

Sickle cell disease is caused by one of the 1200 known hemoglobin variations. A single-point mutation β6(A3)Glu→Val leads to sickling of red blood cells, which in turn causes a lack of oxygen supply to tissue and organs. Although sickle cell disease is well understood, treatment options are currently underdeveloped. The only Food and Drug Administration-approved drug is hydroxyurea, an inducer of fetal γ-hemoglobin, which is known to have a higher oxygen affinity than adult hemoglobins and thus alleviates symptoms. In the search for better cures, Rhesus monkeys (Macaca mulatta) serve as models for monitoring success of induction of fetal γ-hemoglobins and with recent advances in proteomics, MS has become the leading technique to determine globin expression. Similar to humans, Rhesus monkeys possess hemoglobin variants that have not been sufficiently characterized to initiate such a study. Therefore, we developed a combined bottom-up and top-down approach to identify and characterize novel hemoglobin variants of the umbilical cord blood of Rhesus monkeys. A total of four different variants were studied: α, β, γ1 and γ2. A new α- and β-hemoglobin variant was identified, and the two previously hypothesized γ-hemoglobins were identified. In addition, glutathionylation of both γ-hemoglobin variants at their cysteines has been characterized. The combined approach outperformed either bottom-up or top-down alone and can be used for characterization of unknown hemoglobin variants and their PTMs

Mass spectrometric protein maps for biomarker discovery and clinical research

Among the wide range of proteomic technologies, targeted mass spectrometry (MS) has shown great potential for biomarker studies. To extend the degree of multiplexing achieved by selected reaction monitoring (SRM), we recently developed SWATH MS. SWATH MS is a variant of the emerging class of data-independent acquisition (DIA) methods and essentially converts the molecules in a physical sample into perpetually re-usable digital maps. The thus generated SWATH maps are then mined using a targeted data extraction strategy, allowing us to profile disease-related proteomes at a high degree of reproducibility. The successful application of both SRM and SWATH MS requires the a priori generation of reference spectral maps that provide coordinates for quantification. Herein, we demonstrate that the application of the mass spectrometric reference maps and the acquisition of personalized SWATH maps hold a particular promise for accelerating the current process of biomarker discovery

On the development of plasma protein biomarkers

The development of plasma biomarkers has proven to be more challenging than initially anticipated. Many studies have reported lists of candidate proteins rather than validated candidate markers with an assigned performance to a specific clinical objective. Biomarker research necessitates a clear rational framework with requirements on a multitude of levels. On the technological front, the platform needs to be effective to detect low abundant plasma proteins and be able to measure them in a high throughput manner over a large amount of samples reproducibly. At a conceptual level, the choice of the technological platform and available samples should be part of an overall clinical study design that depends on a joint effort between basic and clinical research. Solutions to these needs are likely to facilitate more feasible studies. Targeted proteomic workflows based on SRM mass spectrometry show the potential of fast verification of biomarker candidates in plasma and thereby closing the gap between discovery and validation in the biomarker development pipeline. Biological samples need to be carefully chosen based on well-established guidelines either for candidate discovery in the form of disease models with optimal fidelity to human disease or for candidate evaluation as well-designed and annotated clinical cohort groups. Most importantly, they should be representative of the target population and directly address the investigated clinical question. A conceptual structure of a biomarker study can be provided in the form of several sequential phases, each having clear objectives and predefined goals. Furthermore, guidelines for reporting the outcome of biomarker studies are critical to adequately assess the quality of the research, interpretation and generalization of the results. By being attentive to and applying these considerations, biomarker research should become more efficient and lead to directly translatable biomarker candidates into clinical evaluation

Proteomic Approaches to Study SARS-CoV-2 Biology and COVID-19 Pathology.

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), was declared a pandemic infection in March 2020. As of December 2020, two COVID-19 vaccines have been authorized for emergency use by the U.S. Food and Drug Administration, but there are no effective drugs to treat COVID-19, and pandemic mitigation efforts like physical distancing have had acute social and economic consequences. In this perspective, we discuss how the proteomic research community can leverage technologies and expertise to address the pandemic by investigating four key areas of study in SARS-CoV-2 biology. Specifically, we discuss how (1) mass spectrometry-based structural techniques can overcome limitations and complement traditional structural approaches to inform the dynamic structure of SARS-CoV-2 proteins, complexes, and virions; (2) virus-host protein-protein interaction mapping can identify the cellular machinery required for SARS-CoV-2 replication; (3) global protein abundance and post-translational modification profiling can characterize signaling pathways that are rewired during infection; and (4) proteomic technologies can aid in biomarker identification, diagnostics, and drug development in order to monitor COVID-19 pathology and investigate treatment strategies. Systems-level high-throughput capabilities of proteomic technologies can yield important insights into SARS-CoV-2 biology that are urgently needed during the pandemic, and more broadly, can inform coronavirus virology and host biology

Proteomic Approaches to Study SARS-CoV-2 Biology and COVID-19 Pathology.

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), was declared a pandemic infection in March 2020. As of December 2020, two COVID-19 vaccines have been authorized for emergency use by the U.S. Food and Drug Administration, but there are no effective drugs to treat COVID-19, and pandemic mitigation efforts like physical distancing have had acute social and economic consequences. In this perspective, we discuss how the proteomic research community can leverage technologies and expertise to address the pandemic by investigating four key areas of study in SARS-CoV-2 biology. Specifically, we discuss how (1) mass spectrometry-based structural techniques can overcome limitations and complement traditional structural approaches to inform the dynamic structure of SARS-CoV-2 proteins, complexes, and virions; (2) virus-host protein-protein interaction mapping can identify the cellular machinery required for SARS-CoV-2 replication; (3) global protein abundance and post-translational modification profiling can characterize signaling pathways that are rewired during infection; and (4) proteomic technologies can aid in biomarker identification, diagnostics, and drug development in order to monitor COVID-19 pathology and investigate treatment strategies. Systems-level high-throughput capabilities of proteomic technologies can yield important insights into SARS-CoV-2 biology that are urgently needed during the pandemic, and more broadly, can inform coronavirus virology and host biology