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Manriquez-Sandoval, E.

Publications and source records attributed to Manriquez-Sandoval, E..

3 recordsLinked to original sources

Protein surface chemistry encodes an adaptive resistance to desiccation

Cellular desiccation - the loss of nearly all water from the cell - is a recurring stress in an increasing number of ecosystems that can drive protein unfolding and aggregation. For cells to survive, at least some of the proteome must resume function upon rehydration. Which proteins tolerate desiccation, and the molecular determinants that underlie this tolerance, are largely unknown. Here, we apply quantitative and structural proteomic mass spectrometry to show that certain proteins possess an innate capacity to tolerate rehydration following extreme water loss. Structural analysis points to protein surface chemistry as a key determinant for desiccation tolerance, which we test by showing that rational surface mutants can convert a desiccation sensitive protein into a tolerant one. Desiccation tolerance also has strong overlap with cellular function, with highly tolerant proteins responsible for production of small molecule building blocks, and intolerant proteins involved in energy-consuming processes such as ribosome biogenesis. As a result, the rehydrated proteome is preferentially enriched with metabolite and small molecule producers and depleted of some of the cells heaviest consumers. We propose this functional bias enables cells to kickstart their metabolism and promote cell survival following desiccation and rehydration. TeaserProteins can resist extreme dryness by tuning the amino acids on their surfaces.

biophysics↗

FLiPPR: A Processor for Limited Proteolysis (LiP) Mass Spectrometry Datasets Built on FragPipe

Here, we present FLiPPR, or FragPipe LiP (limited proteolysis) Processor, a tool that facilitates the analysis of data from limited proteolysis mass spectrometry (LiP-MS) experiments following primary search and quantification in FragPipe. LiP-MS has emerged as a method that can provide proteome-wide information on protein structure and has been applied to a range of biological and biophysical questions. Although LiP- MS can be carried out with standard laboratory reagents and mass spectrometers, analyzing the data can be slow and poses unique challenges compared to typical quantitative proteomics workflows. To address this, we leverage the fast, sensitive, and accurate search and label-free quantification algorithms in FragPipe and then process its output in FLiPPR. FLiPPR formalizes a specific data imputation heuristic that carefully uses missing data in LiP-MS experiments to report on the most significant structural changes. Moreover, FLiPPR introduces a new data merging scheme (from ions to cut-sites) and a protein-centric multiple hypothesis correction scheme, collectively enabling processed LiP-MS datasets to be more robust and less redundant. These improvements substantially strengthen statistical trends when previously published data are reanalyzed with the FragPipe/FLiPPR workflow. As a final feature, FLiPPR facilitates the collection of structural metadata to identify correlations between experiments and structural features. We hope that FLiPPR will lower the barrier for more users to adopt LiP-MS, standardize statistical procedures for LiP-MS data analysis, and systematize output to facilitate eventual larger-scale integration of LiP-MS data.

bioinformatics↗

Accurate Protein Domain Structure Annotation with DomainMapper

Automated domain annotation plays a number of important roles in structural informatics and typically involves searching query sequences against Hidden Markov Model (HMM) profiles. This process can be ambiguous or inaccurate when proteins contain domains with non-contiguous residue ranges, and especially when insertional domains are hosted within them. Here we present DomainMapper, an algorithm that accurately assigns a unique domain structure annotation to any query sequence, including those with complex topologies. We validate our domain assignments using the AlphaFold database and confirm that non-contiguity is pervasive (6.5% of all domains in yeast and 2.5% in human). Using this resource, we find that certain folds have strong propensities to be non-contiguous or insertional across the Tree of Life, likely underlying evolutionary preferences for domain topology. DomainMapper is freely available and can be run as a single command line function. HIGHLIGHTSDomainMapper generates a unique domain structure annotation, including non-contiguous and insertional domains Automated annotations of non-contiguous domains are validated against the AlphaFold database DomainMapper can be easily installed and used by non-experts Certain folds have strong preferences to be non-contiguous or insertional GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=188 SRC="FIGDIR/small/484986v1_ufig1.gif" ALT="Figure 1"> View larger version (89K): org.highwire.dtl.DTLVardef@1900be8org.highwire.dtl.DTLVardef@1fdae2borg.highwire.dtl.DTLVardef@1b5bd5corg.highwire.dtl.DTLVardef@a31d56_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗