Search

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease., Graphical abstract, Demichev, Tober-Lau et al., present a time-resolved molecular map of the COVID-19, measuring plasma proteomes of patients with COVID-19 along with an extensive panel of clinical diagnostic parameters at 687-time points. They describe the specificity and dynamics, as well as the predictive and prognostic power of the molecular signatures in COVID-19.

The thermal stability of proteins can be altered when they interact with small molecules. Thus monitoring the thermal stability of proteins under various cellular perturbations can provide insights into protein function, as well as potentially determine drug targets and off-targets. Thermal proteome profiling is a multiplexed mass-spectrommetry method for monitoring the melting behaviour of thousands of proteins in a single experiment. In essence, thermal proteome profiling assumes that proteins denature upon heating and hence become insoluble. Thus, by tracking the relative solubility of proteins at sequentially increasing temperatures, one can report on protein thermal stability. Standard thermodynamics predicts a sigmoidal relationship between temperature and relative solubility and this is the basis of current statistical procedures. However, current methods do not model deviations from this behaviour and they do not quantify uncertainty in the melting profiles. To overcome these challenges, we propose Bayesian functional data analysis tools which allow complex temperature-solubility behaviours. Our methods have improved sensitivity over the state-of-the art, identify new drug-protein associations and have less restrictive assumptions than current approaches. Our methods allows for comprehensive analysis of proteins that deviate from the predicted sigmoid behaviour and we uncover potentially biphasic phenomena with a series of published datasets.

Phosphorylation is a reversible post-translational modification of proteins that controls a plethora of cellular processes and triggers specific physiological responses, for which there is a need to develop tools to characterize phosphorylated targets efficiently. Here, a combinatorial library of triazine-based synthetic ligands comprising 64 small molecules has been rationally designed, synthesized and screened for the enrichment of phosphorylated peptides. The lead candidate (coined A8A3), composed of histidine and phenylalanine mimetic components, showed high binding capacity and selectivity for binding mono- and multi-phosphorylated peptides at pH 3. Ligand A8A3 was coupled onto both cross-linked agarose and magnetic nanoparticles, presenting higher binding capacities (100-fold higher) when immobilized on the magnetic support. The magnetic adsorbent was further screened against a tryptic digest of two phosphorylated proteins (α- and β-caseins) and one non-phosphorylated protein (bovine serum albumin, BSA). The MALDI-TOF mass spectra of the eluted peptides allowed the identification of nine phosphopeptides, comprising both mono- and multi-phosphorylated peptides.

The gel-based proteomics approach is a valuable technique for studying the characteristics of proteins. This technique has diverse applications ranging from analysis of a single protein to the study of the total cellular proteins. Further, protein quality and to some extent distribution can be first assessed by means of one-dimensional gel electrophoresis and then more informatively, for comparative analysis, using the two-dimensional gel electrophoresis technique. Here, we describe how to take advantage of the availability of fluorescent dyes to stain for a selective class of proteins on the same gel for the detection of both phospho- and total proteomes. This enables the co-detection of phosphoproteins as well as total proteins from the same gel and is accomplished by utilizing two different fluorescent stains, the ProQ-Diamond, which stains only phosphorylated proteins, and Sypro Ruby, which stains the entire subset of proteins. This workflow can be applied to gain insights into the regulatory mechanisms induced by signaling molecules such as cyclic nucleotides through the quantification and subsequent identification of responsive phospho- and total proteins.

Phosphoproteomics is a fast-growing field that aims at characterizing phosphorylated proteins in a cell or a tissue at a given time. Phosphorylation of proteins is an important regulatory mechanism in many cellular processes. Gel-free phosphoproteome technique involving enrichment of phosphopeptide coupled with mass spectrometry has proven to be invaluable to detect and characterize phosphorylated proteins. In this chapter, a gel-free quantitative approach involving (15)N metabolic labelling in combination with phosphopeptide enrichment by titanium dioxide (TiO2) and their identification by MS is described. This workflow can be used to gain insights into the role of signalling molecules such as cyclic nucleotides on regulatory networks through the identification and quantification of responsive phospho(proteins).

Using five monoclonal antibodies raised against a human uterine smooth muscle extract, we have identified a novel antigen which runs as a closely spaced doublet in SDS-gels. The proteins (60/63 kDa) co-purify, are present in a 1:1 ratio as judged by Coomassie Blue staining, and are immunologically closely related, if not identical. No N-terminal sequence could be obtained from a mixture of the 60/63 kDa proteins, but the sequence of four polypeptides liberated by V8 protease or cyanogen bromide cleavage showed that the proteins are closely related to the glycolytic enzyme phosphoglucomutase type 1. Affinity-purified polyclonal antibodies and three different monoclonal antibodies to the 60/63 kDa proteins cross-reacted with rabbit skeletal muscle phosphoglucomutase type 1, whilst two additional monoclonal antibodies were specific for the 60/63 kDa proteins. Peptide maps of the 60/63 kDa proteins and phosphoglucomutase 1 are markedly different, and the purified proteins have no detectable phosphoglucomutase activity. Staining of cultured smooth muscle cells and fibroblasts with antibodies to 60/63 kDa proteins showed that the antigen is concentrated in focal contacts at the ends of actin bundles and is also associated with actin filaments. About 60% of the cellular 60/63 kDa proteins were found in the detergent-insoluble fraction, suggesting a physical association with the cytoskeleton. The highest levels of protein immunoreactivity were found in muscles. The antigen is concentrated in muscle adherens junctions, including smooth muscle dense plaques, cardiomyocyte intercalated disks, and striated muscle myotendinous junctions. Among epithelial cells, the 63 kDa isoform of the protein was found only in cultured keratinocytes where immunofluorescent staining was localized in cell-to-cell adherens junctions. Expression of the 60/63 kDa proteins in vascular smooth muscle cells is developmentally regulated and correlates with the differentiated contractile phenotype of these cells.

Whilst the study of yeast genomes and transcriptomes is in an advanced state, there is still much to learn about the resulting proteins in terms of cataloging, characterization of post-translational modifications, turnover, and the dynamics of sub-cellular localization and interactions. Analysis of the transcripts gives little insight into function or diversity as changes in RNA levels do not always correlate with the resulting protein abundance. A number of global and targeted attempts have been made to catalog and characterize the yeast proteome and we describe here the methods used to gain a greater understanding of the yeast proteome. This comprehensive review also describes future approaches that will aid completion in identifying and characterizing the remaining 20% of the undetermined yeast proteome as well as giving new insight into protein dynamics.

Microarrays have revolutionized many areas of biology due to our technical ability to quantify tens of thousands of transcripts within a single experiment. However, there are still many areas that cannot benefit from this technology due to the amount of biological material needed for microarray analysis. In response to this demand, chemistries have been developed that boast the capability of generating targets from nanogram amounts of total RnA, reflecting minimal amounts of biological material, on the order of several hundred or thousand cells. Herein, we describe the evaluation of four chemistries for RnA amplification in terms of reproducibility, sensitivity, accuracy, and comparability to results from a single round of T7 amplification. No evidence for false-positive measurements of differential expression was observed. In contrast, clear differences between chemistries in sensitivity and accuracy were detected. PCR validation showed an interaction of probe sequence on the array and target labeling chemistry, resulting in a chemistry-dependent probe set sensitivity varying over an order of magnitude.