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Freeman, M. R.

Publications and source records attributed to Freeman, M. R..

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Low-background Acyl-biotinyl Exchange Largely Eliminates the Co-isolation of Non-S-acylated Proteins and Enables Deep S-acylproteomic Analysis

Protein S-acylation (also called palmitoylation) is a common post-translational modification whose deregulation plays a key role in the pathogenesis of many diseases. Acyl-biotinyl exchange (ABE), a widely used method for the enrichment of S-acylated proteins, has the potential of capturing the entire S-acylproteome in any types of biological samples. Here, we showed that current ABE methods suffer from high background arising from the co-isolation of non-S-acylated proteins. The background can be substantially reduced by an additional blockage of residual free cysteine residues with 2,2-dithiodipyridine prior to biotin-HPDP reaction. Coupling the low-background ABE (LB-ABE) method with label-free quantitative proteomics, 2,895 high-confidence candidate S-acylated proteins (including 1,591 known S-acylated proteins) were identified from human prostate cancer LNCaP cells, representing so-far the largest S-acylproteome dataset identified in a single study. Immunoblotting analysis confirmed the S-acylation of five known and five novel prostate cancer-related S-acylated proteins in LNCaP cells and suggested that their S-acylation levels were about 0.6-1.8%. In summary, the LB-ABE method largely eliminates the co-isolation of non-S-acylated proteins and enables deep S-acylproteomic analysis. It is expected to facilitate much more comprehensive and accurate quantification of S-acylproteomes than previous ABE methods.

biochemistry

Optimization of DNA extraction from human urinary samples for mycobiome community profiling

IntroductionRecent data suggest the urinary tract hosts a microbial community of varying composition, even in the absence of infection. Culture-independent methodologies, such as next-generation sequencing of conserved ribosomal DNA sequences, provide an expansive look at these communities, identifying both common commensals and fastidious organisms. A fundamental challenge has been the isolation of DNA representative of the entire resident microbial community, including fungi.\n\nMaterials and MethodsWe evaluated multiple modifications of commonly-used DNA extraction procedures using standardized male and female urine samples, comparing resulting overall, fungal and bacterial DNA yields by quantitative PCR. After identifying protocol modifications that increased DNA yields (lyticase/lysozyme digestion, bead beating, boil/freeze cycles, proteinase K treatment, and carrier DNA use), all modifications were combined for systematic confirmation of optimal protocol conditions. This optimized protocol was tested against commercially available methodologies to compare overall and microbial DNA yields, community representation and diversity by next-generation sequencing (NGS).\n\nResultsOverall and fungal-specific DNA yields from standardized urine samples demonstrated that microbial abundances differed significantly among the eight methods used. Methodologies that included multiple disruption steps, including enzymatic, mechanical, and thermal disruption and proteinase digestion, particularly in combination with small volume processing and pooling steps, provided more comprehensive representation of the range of bacterial and fungal species. Concentration of larger volume urine specimens at low speed centrifugation proved highly effective, increasing resulting DNA levels and providing greater microbial representation and diversity.\n\nConclusionsAlterations in the methodology of urine storage, preparation, and DNA processing improve microbial community profiling using culture-independent sequencing methods. Our optimized protocol for DNA extraction from urine samples provided improved fungal community representation. Use of this technique resulted in equivalent representation of the bacterial populations as well, making this a useful technique for the concurrent evaluation of bacterial and fungal populations by NGS.

microbiology