Biology subjects

Katemauswa, M.

Publications and source records attributed to Katemauswa, M..

5 recordsLinked to original sources

bioRxiv2024

Quantification and site-specific analysis of co-occupied N- and O-glycopeptides

Protein glycosylation is a complex post-translational modification that is generally classified as N- or O-linked. Site-specific analysis of glycopeptides is accomplished with a variety of fragmentation methods, depending on the type of glycosylation being investigated and the instrumentation available. For instance, collisional dissociation methods are frequently used for N-glycoproteomic analysis with the assumption that one N-sequon exists per tryptic peptide. Alternatively, electron-based methods are indispensable for O-glycosite localization. However, the presence of simultaneously N- and O-glycosylated peptides could suggest the necessity of electron-based fragmentation methods for N-glycoproteomics, which is not commonly performed. Thus, we quantified the prevalence of N- and O-glycopeptides in mucins and other glycoproteins. A much higher frequency of co-occupancy within mucins was detected whereas only a negligible occurrence occurred within non-mucin glycoproteins. This was demonstrated from analyses of recombinant and/or purified proteins, as well as more complex samples. Where co-occupancy occurred, O-glycosites were frequently localized to the Ser/Thr within the N-sequon. Additionally, we found that O-glycans in close proximity to the occupied Asn were predominantly unelaborated core 1 structures, while those further away were more extended. Overall, we demonstrate electron-based methods are required for robust site-specific analysis of mucins, wherein co-occupancy is more prevalent. Conversely, collisional methods are generally sufficient for analyses of other types of glycoproteins. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/602348v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@b14908org.highwire.dtl.DTLVardef@131e812org.highwire.dtl.DTLVardef@17b07cborg.highwire.dtl.DTLVardef@3cb199_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2023

Persistent biofluid small molecule alterations induced by Trypanosoma cruzi infection are not restored by antiparasitic treatment

Table of contents graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/543565v1_figu1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@10c3a0aorg.highwire.dtl.DTLVardef@1b69d6dorg.highwire.dtl.DTLVardef@199867org.highwire.dtl.DTLVardef@64b20b_HPS_FORMAT_FIGEXP M_FIG C_FIG Chagas Disease (CD), caused by Trypanosoma cruzi (T. cruzi) protozoa, is a complicated parasitic illness with inadequate medical measures for diagnosing infection and monitoring treatment success. To address this gap, we analyzed changes in the metabolome of T. cruzi-infected mice via liquid chromatography tandem mass spectrometry analysis of clinically-accessible biofluids: saliva, urine, and plasma. Urine was the most indicative of infection status, across mouse and parasite genotypes. Metabolites perturbed by infection in the urine include kynurenate, acylcarnitines, and threonylcarbamoyladenosine. Based on these results, we sought to implement urine as a tool for assessment of CD treatment success. Strikingly, it was found that mice with parasite clearance following benznidazole antiparasitic treatment had comparable overall urine metabolome to mice that failed to clear parasites. These results match with clinical trial data in which benznidazole treatment did not improve patient outcomes in late-stage disease. Overall, this study provides insights into new small molecule-based CD diagnostic methods and a new approach to assess functional treatment response.

microbiology↗

bioRxiv2021

Optimized extraction method enables quantitative analysis of surface metabolite recovery for exposomics and behavioral studies

Workplace chemical exposures are a major source of occupational injury. Although over half of these are skin exposures, exposomics research often focuses on chemical levels in the air or in worker biofluids such as blood and urine. Until now, one limitation has been the lack of methods to quantitatively measure surface chemical transfer. Outside the realm of harmful chemicals, the small molecules we leave behind on surfaces can also reveal important aspects of human behavior. In this study, we developed a swab-based quantitative approach to determine small molecule concentrations across common surfaces. We demonstrate its utility using one drug, cyclobenzaprine, and two human-derived metabolites, carnitine and phenylacetylglutamine, on four common surfaces: linoleum flooring, plastified laboratory workbench, metal and Plexiglass. This approach enabled linear small molecule recovery and quantification of molecule abundance on workplace built environment surfaces. Overall, this method paves the way for future quantitative exposomics studies.

biochemistry↗

bioRxiv2021

The Core Human Fecal Metabolome

Summary ParagraphAmong the biomolecules at the center of human health and molecular biology is a system of molecules that defines the human phenotype known as the metabolome. Through an untargeted metabolomic analysis of fecal samples from human individuals from Africa and the Americas--the birthplace and the last continental expansion of our species, respectively--we present the characterization of the core human fecal metabolome. The majority of detected metabolite features were ubiquitous across populations, despite any geographic, dietary, or behavioral differences. Such shared metabolite features included hyocholic acid and cholesterol. However, any characterization of the core human fecal metabolome is insufficient without exploring the influence of industrialization. Here, we show chemical differences along an industrialization gradient, where the degree of industrialization correlates with metabolomic changes. We identified differential metabolite features like leucyl-leucine dipeptides and urobilin as major metabolic correlates of these behavioral shifts. Our results indicate that industrialization significantly influences the human fecal metabolome, but diverse human lifestyles and behavior still maintain a core human fecal metabolome. This study represents the first characterization of the core human fecal metabolome through untargeted analyses of populations along an industrialization gradient.

biochemistry↗

bioRxiv2019

3D mapping of host-parasite-microbiome interactions reveals metabolic determinants of tissue tropism and disease tolerance in Chagas disease

Chagas disease (CD) is a parasitic infection caused by Trypanosoma cruzi protozoa. Over 8 million people worldwide are T. cruzi-positive, 20-30% of which will develop cardiomyopathy, megaoesophagus and/or megacolon. The mechanisms leading to gastrointestinal (GI) symptom development are however poorly understood. To address this issue, we systematically characterized the spatial impact of experimental T. cruzi infection on the microbiome and metabolome across the GI tract. The largest microbiota perturbations were observed in the proximal large intestine in both acute and chronic disease, with chronic-stage effects also observed in the cecum. Strikingly, metabolomic impact of acute-to-chronic stage transition differed depending on the organ, with persistent large-scale effects of infection primarily in the oesophagus and large intestine, providing a potential mechanism for GI pathology tropism in CD. Infection particularly affected acylcarnitine and lipid metabolism. Building on these observations, treatment of infected mice with carnitine-supplemented drinking water prevented acute-stage mortality with no changes in parasite burden. Overall, these results identified a new mechanism of disease tolerance in CD, with potential for the development of new therapeutic regimens. More broadly, these results highlight the potential of spatially-resolved metabolomic approaches to provide insight into disease pathogenesis, with translational applications for infectious disease drug development.

microbiology↗