Proximity Extension Assay in Combination with Next-Generation Sequencing for High-throughput Proteome-wide Analysis.

Understanding the dynamics of the human proteome is crucial for developing biomarkers to be used as measurable indicators for disease severity and progression, patient stratification, and drug development. The Proximity Extension Assay (PEA) is a technology that translates protein information into actionable knowledge by linking protein-specific antibodies to DNA-encoded tags. In this report we demonstrate how we have combined the unique PEA technology with an innovative and automated sample preparation and high-throughput sequencing readout enabling parallel measurement of nearly 1500 proteins in 96 samples generating close to 150,000 data points per run. This advancement will have a major impact on the discovery of new biomarkers for disease prediction and prognosis and contribute to the development of the rapidly evolving fields of wellness monitoring and precision medicine.

Differential Plasma Protein Regulation and Statin Effects in Human Immunodeficiency Virus (HIV)-Infected and Non-HIV-Infected Patients Utilizing a Proteomics Approach.

BACKGROUND: People with human immunodeficiency virus (PWH) demonstrate increased atherosclerotic cardiovascular disease (ASCVD). Statins are being studied to prevent ASCVD in human immunodeficiency virus (HIV), but little is known regarding the effects of statins on a broad range of inflammatory and cardiovascular proteins in this population. METHODS: We used a highly specific discovery proteomic approach (Protein Extension Assay), to determine statin effects on over 350 plasma proteins in relevant ASCVD pathways among HIV and non-HIV groups. Responses to pitavastatin calcium were assessed in 89 PWH in the INTREPID trial and 46 non-HIV participants with features of central adiposity and insulin resistance. History of cardiovascular disease was exclusionary for both studies. RESULTS: Among participants with HIV, PCOLCE (enzymatic cleavage of type I procollagen) significantly increased after pitavastatin therapy and PLA2G7 (systemic marker of arterial inflammation) decreased. Among participants without HIV, integrin subunit alpha M (integrin adhesive function) and defensin alpha-1 (neutrophil function) increased after pitavastatin therapy and PLA2G7 decreased. At baseline, comparing participants with and without HIV, differentially expressed proteins included proteins involved in platelet and endothelial function and immune activation. CONCLUSIONS: Pitavastatin affected proteins important to platelet and endothelial function and immune activation, and effects differed to a degree within PWH and participants without HIV.

In situ detection and genotyping of individual mRNA molecules.

Increasing knowledge about the heterogeneity of mRNA expression within cell populations highlights the need to study transcripts at the level of single cells. We present a method for detection and genotyping of individual transcripts based on padlock probes and in situ target-primed rolling-circle amplification. We detect a somatic point mutation, differentiate between members of a gene family and perform multiplex detection of transcripts in human and mouse cells and tissue.

Glycosylases and AP-cleaving enzymes as a general tool for probe-directed cleavage of ssDNA targets.

The current arsenal of molecular tools for site-directed cleavage of single-stranded DNA (ssDNA) is limited. Here, we describe a method for targeted DNA cleavage that requires only the presence of an A nucleotide at the target position. The procedure involves hybridization of a complementary oligonucleotide probe to the target sequence. The probe is designed to create a deliberate G:A mismatch at the desired position of cleavage. The DNA repair enzyme MutY glycosylase recognizes the mismatch structure and selectively removes the mispaired A from the duplex to create an abasic site in the target strand. Addition of an AP-endonuclease, such as Endonuclease IV, subsequently cleaves the backbone dividing the DNA strand into two fragments. With an appropriate choice of an AP-cleaving enzyme, the 3'- and 5'-ends of the cleaved DNA are suitable to take part in subsequent enzymatic reactions such as priming for polymerization or joining by DNA ligation. We define suitable standard reaction conditions for glycosylase/AP-cleaving enzyme (G/AP) cleavage, and demonstrate the use of the method in an improved scheme for in situ detection using target-primed rolling-circle amplification of padlock probes.

Plasma ACE2 predicts outcome of COVID-19 in hospitalized patients.

AIMS: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) binds to angiotensin converting enzyme 2 (ACE2) enabling entrance of the virus into cells and causing the infection termed coronavirus disease of 2019 (COVID-19). Here, we investigate associations between plasma ACE2 and outcome of COVID-19. METHODS AND RESULTS: This analysis used data from a large longitudinal study of 306 COVID-19 positive patients and 78 COVID-19 negative patients (MGH Emergency Department COVID-19 Cohort). Comprehensive clinical data were collected on this cohort, including 28-day outcomes. The samples were run on the Olink® Explore 1536 platform which includes measurement of the ACE2 protein. High admission plasma ACE2 in COVID-19 patients was associated with increased maximal illness severity within 28 days with OR = 1.8, 95%-CI: 1.4-2.3 (P < 0.0001). Plasma ACE2 was significantly higher in COVID-19 patients with hypertension compared with patients without hypertension (P = 0.0045). Circulating ACE2 was also significantly higher in COVID-19 patients with pre-existing heart conditions and kidney disease compared with patients without these pre-existing conditions (P = 0.0363 and P = 0.0303, respectively). CONCLUSION: This study suggests that measuring plasma ACE2 is potentially valuable in predicting COVID-19 outcomes. Further, ACE2 could be a link between COVID-19 illness severity and its established risk factors hypertension, pre-existing heart disease and pre-existing kidney disease.

Longitudinal proteomic analysis of severe COVID-19 reveals survival-associated signatures, tissue-specific cell death, and cell-cell interactions.

Mechanisms underlying severe coronavirus disease 2019 (COVID-19) disease remain poorly understood. We analyze several thousand plasma proteins longitudinally in 306 COVID-19 patients and 78 symptomatic controls, uncovering immune and non-immune proteins linked to COVID-19. Deconvolution of our plasma proteome data using published scRNA-seq datasets reveals contributions from circulating immune and tissue cells. Sixteen percent of patients display reduced inflammation yet comparably poor outcomes. Comparison of patients who died to severely ill survivors identifies dynamic immune-cell-derived and tissue-associated proteins associated with survival, including exocrine pancreatic proteases. Using derived tissue-specific and cell-type-specific intracellular death signatures, cellular angiotensin-converting enzyme 2 (ACE2) expression, and our data, we infer whether organ damage resulted from direct or indirect effects of infection. We propose a model in which interactions among myeloid, epithelial, and T cells drive tissue damage. These datasets provide important insights and a rich resource for analysis of mechanisms of severe COVID-19 disease.

Plasma proteomics reveals tissue-specific cell death and mediators of cell-cell interactions in severe COVID-19 patients.

COVID-19 has caused over 1 million deaths globally, yet the cellular mechanisms underlying severe disease remain poorly understood. By analyzing several thousand plasma proteins in 306 COVID-19 patients and 78 symptomatic controls over serial timepoints using two complementary approaches, we uncover COVID-19 host immune and non-immune proteins not previously linked to this disease. Integration of plasma proteomics with nine published scRNAseq datasets shows that SARS-CoV-2 infection upregulates monocyte/macrophage, plasmablast, and T cell effector proteins. By comparing patients who died to severely ill patients who survived, we identify dynamic immunomodulatory and tissue-associated proteins associated with survival, providing insights into which host responses are beneficial and which are detrimental to survival. We identify intracellular death signatures from specific tissues and cell types, and by associating these with angiotensin converting enzyme 2 (ACE2) expression, we map tissue damage associated with severe disease and propose which damage results from direct viral infection rather than from indirect effects of illness. We find that disease severity in lung tissue is driven by myeloid cell phenotypes and cell-cell interactions with lung epithelial cells and T cells. Based on these results, we propose a model of immune and epithelial cell interactions that drive cell-type specific and tissue-specific damage in severe COVID-19.

Novel mediators of statin effects on plaque in HIV: a proteomics approach.

OBJECTIVE: HIV patients have increased atherosclerotic coronary vascular disease (ASCVD), thought to be mediated through inflammatory mechanisms. We hypothesized that among asymptomatic HIV-infected patients with subclinical coronary plaque, statin therapy would modulate unique inflammatory and cardiovascular proteins in relation to change in subclinical coronary plaque volume. We tested this hypothesis using a novel proteomics approach. DESIGN: Forty HIV-infected participants were randomized to atorvastatin (40 mg/day) versus placebo, and underwent computed tomography coronary angiography to quantify plaque volume at baseline and 1 year. METHODS: We used Olink Cardiovascular III and Cardiometabolic panels based on dual antibody epitope recognition with linked DNA amplification to compare change over time in 184 proteins in treatment versus placebo and in relation to change in coronary plaque volume. RESULTS: Six proteins (TFPI, CCL24, NT-Pro BNP, MBL2, LTBR, PCOLCE) changed significantly in the atorvastatin versus placebo group, many in innate immune and other novel inflammatory pathways. Twenty-six proteins changed significantly in relationship to total coronary plaque volume over 1 year. Notably, many of these proteins changed only weakly in relationship to change in low-density lipoprotein (LDL). Overlapping these two broad discovery approaches, proteins involved in myocardial fibrosis/collagen formation and monocyte chemoattraction changed with statin treatment, in relationship to plaque volume, but not LDL. CONCLUSION: This proof-of-concept study employing a proteomic discovery platform offers insight into statin effects on novel immune pathways relevant to ASCVD progression in HIV. Novel biomarker discovery may enhance precision medicine strategies to estimate the efficacy of targeted therapies to reduce ASCVD progression and events in HIV.

Assessing statin effects on cardiovascular pathways in HIV using a novel proteomics approach: Analysis of data from INTREPID, a randomized controlled trial.

BACKGROUND: People with HIV (PWH) demonstrate increased cardiovascular disease (CVD), due in part to increased immune activation, inflammation, and endothelial dysfunction. METHODS: In a randomized trial (INTREPID), 252 HIV-infected participants with dyslipidemia and no history of coronary artery disease were randomized (1:1) to pitavastatin 4 mg vs. pravastatin 40 mg for 52 weeks. Using a proteomic discovery approach, 92 proteins biomarkers were assessed using Proximity Extension Assay technology to determine the effects of statins on key atherosclerosis and CVD pathways among PWH. 225 participants had specimens available for biomarker analysis pre- and post-baseline. FINDINGS: The mean age was 49.5 ±â€¯8.0 (mean ±â€¯SD), LDL-C 155 ±â€¯25 mg/dl and CD4 count 620 ±â€¯243 cell/mm3. Among all participants, three proteins significantly decreased: tissue factor pathway inhibitor [TFPI; t-statistic = -6.38, FDR p-value<0.0001], paraoxonase 3 [PON3; t-statistic = -4.64, FDR p-value = 0.0003], and LDL-receptor [LDLR; t-statistic = -4.45, FDR p-value = 0.0004]; and two proteins significantly increased galectin-4 [Gal-4; t-statistic = 3.50, FDR p-value = 0.01] and insulin-like growth factor binding protein 2 [IGFBP-2; t-statistic = 3.21, FDR p-value = 0.03]. The change in TFPI was significantly different between the pitavastatin and pravastatin groups. Among all participants, change in TFPI related to the change in LDL-C (r = 0.43, P < 0.0001) and change in Lp-PLA2 (r = 0.29, P < 0.0001). INTERPRETATION: Using a proteomics approach, we demonstrated that statins led to a significant reduction in the levels of TFPI, PON3, and LDLR and an increase in Gal-4 and IGFBP-2, key proteins involved in coagulation, redox signaling, oxidative stress, and glucose metabolism. Pitavastatin led to a greater reduction in TFPI than pravastatin. These data highlight potential novel mechanisms of statin effects among PWH. FUND: This work was supported by an investigator-initiated grant to S.K.G. from KOWA Pharmaceuticals America, Inc. and the National Institutes of Health [P30 DK040561; Nutrition Obesity Research Center at Harvard]. M.T. was support by National Institutes of Health [5KL2TR001100-05; Harvard Catalyst KL2 grant].

Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors.

Dendritic cells (DCs) and monocytes play a central role in pathogen sensing, phagocytosis, and antigen presentation and consist of multiple specialized subtypes. However, their identities and interrelationships are not fully understood. Using unbiased single-cell RNA sequencing (RNA-seq) of ~2400 cells, we identified six human DCs and four monocyte subtypes in human blood. Our study reveals a new DC subset that shares properties with plasmacytoid DCs (pDCs) but potently activates T cells, thus redefining pDCs; a new subdivision within the CD1C+ subset of DCs; the relationship between blastic plasmacytoid DC neoplasia cells and healthy DCs; and circulating progenitor of conventional DCs (cDCs). Our revised taxonomy will enable more accurate functional and developmental analyses as well as immune monitoring in health and disease.

Alternative splicing of the chromodomain protein Morf4l1 pre-mRNA has implications on cell differentiation in the developing chicken retina.

The proliferation, cell cycle exit and differentiation of progenitor cells are controlled by several different factors. The chromodomain protein mortality factor 4-like 1 (Morf4l1) has been ascribed a role in both proliferation and differentiation. Little attention has been given to the existence of alternative splice variants of the Morf4l1 mRNA, which encode two Morf41l isoforms: a short isoform (S-Morf4l1) with an intact chromodomain and a long isoform (L-Morf4l1) with an insertion in or in the vicinity of the chromodomain. The aim of this study was to investigate if this alternative splicing has a function during development. We analysed the temporal and spatial distribution of the two mRNAs and over-expressed both isoforms in the developing retina. The results showed that the S-Morf4l1 mRNA is developmentally regulated. Over-expression of S-Morf4l1 using a retrovirus vector produced a clear phenotype with an increase of early-born neurons: retinal ganglion cells, horizontal cells and cone photoreceptor cells. Over-expression of L-Morf4l1 did not produce any distinguishable phenotype. The over-expression of S-Morf4l1 but not L-Morf4l1 also increased apoptosis in the infected regions. Our results suggest that the two Morf4l1 isoforms have different functions during retinogenesis and that Morf4l1 functions are fine-tuned by developmentally regulated alternative splicing. The data also suggest that Morf4l1 contributes to the regulation of cell genesis in the retina.

In situ mutation detection and visualization of intratumor heterogeneity for cancer research and diagnostics.

Current assays for somatic mutation analysis are based on extracts from tissue sections that often contain morphologically heterogeneous neoplastic regions with variable contents of normal stromal and inflammatory cells, obscuring the results of the assays. We have developed an RNA-based in situ mutation assay that targets oncogenic mutations in a multiplex fashion that resolves the heterogeneity of the tissue sample. Activating oncogenic mutations are targets for a new generation of cancer drugs. For anti-EGFR therapy prediction, we demonstrate reliable in situ detection of KRAS mutations in codon 12 and 13 in colon and lung cancers in three different types of routinely processed tissue materials. High-throughput screening of KRAS mutation status was successfully performed on a tissue microarray. Moreover, we show how the patterns of expressed mutated and wild-type alleles can be studied in situ in tumors with complex combinations of mutated EGFR, KRAS and TP53. This in situ method holds great promise as a tool to investigate the role of somatic mutations during tumor progression and for prediction of response to targeted therapy.

In situ detection of individual mRNA molecules and protein complexes or post-translational modifications using padlock probes combined with the in situ proximity ligation assay.

Analysis at the single-cell level is essential for the understanding of cellular responses in heterogeneous cell populations, but it has been difficult to perform because of the strict requirements put on detection methods with regard to selectivity and sensitivity (i.e., owing to the cross-reactivity of probes and limited signal amplification). Here we describe a 1.5-d protocol for enumerating and genotyping mRNA molecules in situ while simultaneously obtaining information on protein interactions or post-translational modifications; this is achieved by combining padlock probes with in situ proximity ligation assays (in situ PLA). In addition, we provide an example of how to design padlock probes and how to optimize staining conditions for fixed cells and tissue sections. Both padlock probes and in situ PLA provide the ability to directly visualize single molecules by standard microscopy in fixed cells or tissue sections, and these methods may thus be valuable for both research and diagnostic purposes.

Methods for analysis of the cancer microenvironment and their potential for disease prediction, monitoring and personalized treatments.

A tumor does not consist of a homogenous population of cancer cells. Therefore, to understand cancer, the tumor microenvironment and the interplay between the different cell types present in the tumor has to be taken into account, and how this regulates the growth and survival of the cancer cells. To achieve a full picture of this complex interplay, analysis of tumor tissue should ideally be performed with cellular resolution, providing activity status of individual cells in this heterogeneous population of different cell-types. In addition, in situ analysis provides information on the architecture of the tissue wherein the cancer cells thrive, providing information of the identity of neighboring cells that can be used to understand cell-cell communication. Herein we describe how padlock probes and in situ PLA can be used for visualization of nucleic acids and protein activity, respectively, directly in tissue sections, and their potential future role in personalized medicine.

Simultaneous visualization of both signaling cascade activity and end-point gene expression in single cells.

We have developed an approach for simultaneous detection of individual endogenous protein modifications and mRNA molecules in single cells in situ. For this purpose we combined two methods previously developed in our lab: in situ proximity ligation assay for the detection of individual protein interactions and -modifications and in situ detection of single mRNA molecules using padlock probes. As proof-of-principle, we demonstrated the utility of the method for simultaneous detection of phosphorylated PDGFRß and DUSP6/MKP-3 mRNA molecules in individual human fibroblasts upon PDGF-BB stimulation. Further we applied drugs disrupting the PDGFRß signaling pathway at various sites to show that this combined method can concurrently monitor the molecular effect of the drugs, i.e. inhibition of downstream signaling from the targeted node in the signaling pathway. Due to its ability to detect different types of molecules in single cells in situ the method presented here can contribute to a deeper understanding of cell-to-cell variations and can be applied to e.g. pinpoint effector sites of drugs in a signaling pathway.