Functional characterization of 3D protein structures informed by human genetic diversity

Sequence variation data of the human proteome can be used to analyze 3D protein structures to derive functional insights. We used genetic variant data from nearly 140,000 individuals to analyze 3D positional conservation in 4,715 proteins and 3,951 homology models using 860,292 missense and 465,886 synonymous variants. Sixty percent of protein structures harbor at least one intolerant 3D site as defined by significant depletion of observed over expected missense variation. Structural intolerance data correlated with deep mutational scanning functional readouts for PPARG, MAPK1/ERK2, UBE2I, SUMO1, PTEN, CALM1, CALM2, and TPK1 and with shallow mutagenesis data for 1,026 proteins. The 3D structural intolerance analysis revealed different features for ligand binding pockets and orthosteric and allosteric sites. Large-scale data on human genetic variation support a definition of functional 3D sites proteome-wide.

Proteome Digestion Specificity Analysis for Rational Design of Extended Bottom-up and Middle-down Proteomics Experiments

Unige Anna Laskay, Kristina Srzentic, Yury Tsybin

Mass spectrometry (MS)-based bottom-up proteomics (BUP) is currently the method of choice for large-scale identification and characterization of proteins present in complex samples, such as cell lysates, body fluids, or tissues. Technically, BUP relies on MS analysis of complex mixtures of small, 15 kDa (TDP). Because of instrumentation-related considerations, we first advocate for the extended BUP approach as the potential near-future improvement of BUP. Therefore, we chose to optimize the number of unique peptides in the 3-7 kDa range while maximizing the number of represented proteins. The present study considers human, yeast, and bacterial proteomes. Results of the study can be further used for designing extended BUP or MDP experimental workflows.

Amer Chemical Soc2013

TEMPLE: analysing population genetic variation at transcription factor binding sites

Stefan Jean Laurent, Maria Litovchenko

Genetic variation occurring at the level of regulatory sequences can affect phenotypes and fitness in natural populations. This variation can be analysed in a population genetic framework to study how genetic drift and selection affect the evolution of these functional elements. However, doing this requires a good understanding of the location and nature of regulatory regions and has long been a major hurdle. The current proliferation of genomewide profiling experiments of transcription factor occupancies greatly improves our ability to identify genomic regions involved in specific DNA-protein interactions. Although software exists for predicting transcription factor binding sites (TFBS), and the effects of genetic variants on TFBS specificity, there are no tools currently available for inferring this information jointly with the genetic variation at TFBS in natural populations. We developed the software Transcription Elements Mapping at the Population LEvel (TEMPLE), which predicts TFBS, evaluates the effects of genetic variants on TFBS specificity and summarizes the genetic variation occurring at TFBS in intraspecific sequence alignments. We demonstrate that TEMPLE's TFBS prediction algorithms gives identical results to PATSER, a software distribution commonly used in the field. We also illustrate the unique features of TEMPLE by analysing TFBS diversity for the TF Senseless (SENS) in one ancestral and one cosmopolitan population of the fruit fly Drosophila melanogaster. TEMPLE can be used to localize TFBS that are characterized by strong genetic differentiation across natural populations. This will be particularly useful for studies aiming to identify adaptive mutations. TEMPLE is a java-based cross-platform software that easily maps the genetic diversity at predicted TFBSs using a graphical interface, or from the Unix command line.

Wiley-Blackwell2016

Differential Visual Proteomics: Enabling the Proteome-Wide Comparison of Protein Structures of Single-Cells

Henning Paul-Julius Stahlberg, Anastasia Syntychaki

Proteins are involved in all tasks of life, and their characterization is essential to understand the underlying mechanisms of biological processes. We present a method called "differential visual proteomics" geared to study proteome-wide structural changes of proteins and protein-complexes between a disturbed and an undisturbed cell or between two cell populations. To implement this method, the cells are lysed and the lysate is prepared in a lossless manner for single-particle electron microscopy (EM). The samples are subsequently imaged in the EM. Individual particles are computationally extracted from the images and pooled together, while keeping track of which particle originated from which specimen. The extracted particles are then aligned and classified. A final quantitative analysis of the particle classes found identifies the particle structures that differ between positive and negative control samples. The algorithm and a graphical user interface developed to perform the analysis and to visualize the results were tested with simulated and experimental data. The results are presented, and the potential and limitations of the current implementation are discussed. We envisage the method as a tool for the untargeted profiling of the structural changes in the proteome of single-cells as a response to a disturbing force.

American Chemical Society (ACS)2019

TEMPLE: analysing population genetic variation at transcription factor binding sites

Stefan Jean Laurent, Maria Litovchenko

Wiley-Blackwell2016