Biology subjects

Kelly, M. S.

Publications and source records attributed to Kelly, M. S..

4 recordsLinked to original sources

bioRxiv2023

Searching for Structure: Characterizing the Protein Conformational Landscape with Clustering-based Algorithms

The identification and characterization of the main conformations from a protein population is a challenging, inherently high-dimensional problem. We introduce the Secondary sTructural Ensembles with machine LeArning (StELa) double clustering method, which clusters protein structures based on the underlying Ramachandran plot. Our approach takes advantage of the relationship between the phi and psi dihedral angles in a protein backbone and the secondary structure of the protein. The classification of states as vectors composed of the clusters indices arising naturally from the Ramachandran plot, followed by the hierarchical clustering of the vectors, enables the identification of the minima from the corresponding free energy landscape (FEL) by lifting the high structure degeneracy found with existing approaches such as the RMSD-based clustering GROMOS. We compare the performance of StELa with not only GROMOS but also with CATS, the combinatorial averaged transient structure clustering method based on distributions of the phi and psi dihedral angle coordinates. Using ensembles of conformations from molecular dynamics (MD) simulations of either intrinsically disordered proteins (IDPs) of various lengths (tau protein fragments) or from local structures from a globular protein, we show that StELa is the only clustering method that identifies nearly all the minima from the corresponding FELs. In contrast, GROMOS yields a large number of clusters that cover the entire FEL and CATS, even with an additional clustering step, is unable to sample well the FEL for long IDPs and for fragments from globular proteins as it misses important minima. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/557631v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@634f90org.highwire.dtl.DTLVardef@1fca966org.highwire.dtl.DTLVardef@d59bd9org.highwire.dtl.DTLVardef@1eadb94_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2023

Comprehensive Assessment of the Intrinsic Pancreatic Microbiome

BackgroundSmall studies in pancreatic ductal adenocarcinoma (PDAC) and intraductal papillary mucinous neoplasm (IPMN) have suggested that intra-pancreatic microbial dysbiosis may drive malignant transformation. We sought to comprehensively profile tissue and cyst fluid in patients with benign, precancerous, and cancerous conditions of the pancreas to characterize the intrinsic pancreatic microbiome. MethodsPancreatic samples were collected at the time of resection from 109 patients. Samples included tumor tissue (control, n=20; IPMN, n=20; PDAC, n=19) and pancreatic cyst fluid (IPMN, n=30; SCA, n=10; MCN, n=10). Assessment of bacterial DNA by quantitative PCR and 16S ribosomal RNA gene sequencing was performed. Downstream analyses determined the relative abundances of individual taxa between groups and compared intergroup diversity. Whole-genome sequencing data from 140 patients with PDAC in the National Cancer Institutes Clinical Proteomic Tumor Analysis Consortium (CPTAC) were analyzed to validate findings. ResultsSequencing of pancreatic tissue yielded few microbial reads regardless of diagnosis, and analysis of pancreatic tissue showed no difference in the abundance and composition of bacterial taxa between normal pancreas, IPMN, or PDAC groups. Low-grade dysplasia (LGD) and high-grade dysplasia (HGD) IPMN were characterized by low bacterial abundances with no difference in tissue composition and a slight increase in Pseudomonas and Sediminibacterium in HGD cyst fluid. Decontamination analysis using the CPTAC database confirmed a low-biomass, low-diversity intrinsic pancreatic microbiome that did not differ by pathology. ConclusionsOur analysis of the pancreatic microbiome demonstrated very low intrinsic biomass that is relatively conserved across diverse neoplastic conditions and thus unlikely to drive malignant transformation. Significance of this studyO_ST_ABSWhat is already known on this subject?C_ST_ABSO_LIMicrobial colonization, infection, and dysbiosis have been implicated in the oncogenesis of various gastrointestinal tumors (e.g.: Helicobacter pylori in gastric cancer, hepatitis B and C in hepatocellular carcinoma, colon dysbiosis in colon cancer progression). C_LIO_LIFew studies have analyzed the intrinsic pancreatic microbiome, and these have produced conflicting results regarding microbial presence and alterations associated with malignant disease. C_LIO_LIIPMN is a precursor lesion to pancreatic cancer that represents a whole gland defect without an established driver event, and microbiome changes have been implicated as a possible etiology of cyst formation and dysplastic progression. C_LI What are the new findings?O_LIA low-biomass, low-diversity intrinsic pancreatic microbiome is present in both pancreatic tissue and cyst fluid. C_LIO_LIThis intrinsic pancreatic microbiome does not differ in terms of abundance, composition, or diversity between patients with PDAC, IPMN, or other benign conditions of the pancreas. C_LI How might it impact clinical practice in the foreseeable future?O_LIMicrobiome dysbiosis does not appear to be a driver of malignant degeneration of IPMN, and further research is needed to identify drivers of oncogenesis in order for possible chemoprevention strategies to be developed. C_LI

microbiology↗

bioRxiv2022

Microtubule severing enzymes oligomerization and allostery: a tale of two domains

Severing proteins are nanomachines from the AAA+ (ATPases associated with various cellular activities) superfamily whose function is to remodel the largest cellular filaments, microtubules. The standard AAA+ machines adopt hexameric ring structures for functional reasons, while being primarily monomeric in the absence of the nucleotide. Both major severing proteins, katanin and spastin, are believed to follow this trend. However, studies proposed that they populate lower-order oligomers in the presence of co-factors, which are functionally relevant. Our simulations show that the preferred oligomeric assembly is dependent on the binding partners, and on the type of severing protein. Essential dynamics analysis predicts that the stability of an oligomer is dependent on the strength of the interface between the helical bundle domain (HBD) of a monomer and the convex face of the nucleotide binding domain (NBD) of a neighboring monomer. Hot spots analysis found that the region consisting of the HBD tip and the C-terminal (CT) helix is the only common element between the allosteric networks responding to nucleotide, substrate, and inter-monomer binding. Clustering analysis indicates the existence of multiple pathways for the transition between the secondary structure of the HBD tip in monomers and the structure(s) it adopts in oligomers.

biophysics↗

bioRxiv2022

Exploring the effect of mechanical anisotropy of protein structures in the unfoldase mechanism of AAA+ molecular machines

Essential cellular processes of microtubule disassembly and protein degradation, which span lengths from tens of m to nm, are mediated by specialized molecular machines with similar hexameric structure and function. Our molecular simulations at atomistic and coarse-grained scales show that both the microtubule severing protein spastin and the caseinolytic protease ClpY, accomplish spectacular unfolding of their diverse substrates, a microtubule lattice and dihydrofolate reductase (DHFR), by taking advantage of mechanical anisotropy in these proteins. By considering wild-type and variants of DHFR, we found that optimal ClpY-mediated action probes favorable orientations of the substrate relative to the machine. Unfolding of wild-type DHFR involves strong mechanical interfaces near each terminal and occurs along branched pathways, whereas unfolding of DHFR variants involves softer mechanical interfaces and occurs through single pathways, but translocation hindrance can arise from internal mechanical resistance. For spastin, optimum severing action initiated by pulling on a tubulin subunit is achieved through the orientation of the machine versus the substrate (microtubule lattice). Moreover, changes in the strength of the interactions between spastin and a microtubule filament, which can be driven by the tubulin code, lead to drastically different outcomes for the integrity of the hexameric structure of the machine.

biophysics↗