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Extracellular vesicles (EVs) are of growing interest due to their potential diagnostic, disease surveillance, and therapeutic applications. While several studies have evaluated EV isolation methods in various biofluids, there are few if any data on these techniques when applied to stool. The latter is an ideal biospecimen for studying EVs and colorectal cancer (CRC) because the release of tumour markers by luminal exfoliation into stool occurs earlier than vascular invasion. Since EV release is a conserved mechanism, bacteria in stool contribute to the overall EV population. In this study, we assessed five EV separation methods (ultracentrifugation [UC], precipitation [EQ‐O, EQ‐TC], size exclusion chromatography [SEC], and ultrafiltration [UF]) for total recovery, reproducibility, purity, RNA composition, and protein expression in stool supernatant. CD63, TSG101, and ompA proteins were present in EV fractions from all methods except UC. Human (18s) and bacterial (16s) rRNA was detected in stool EV preparations. Enzymatic treatment prior to extraction is necessary to avoid non‐vesicular RNA contamination. Ultrafiltration had the highest recovery, RNA, and protein yield. After assessing purity further, SEC was the isolation method of choice. These findings serve as the groundwork for future studies that use high throughput omics technologies to investigate the potential of stool‐derived EVs as a source for novel biomarkers for early CRC detection.

Regular screening for colorectal cancer (CRC) is critical for early detection and long-term survival. Despite the current screening options available and advancements in therapies there will be around 53,000 CRC related deaths this year. There is great interest in non-invasive alternatives such as plasma cell-free RNA (cfRNA) for diagnostic, prognostic, and predictive applications. In the current study, our aim was to identify and validate potential cfRNA candidates to improve early CRC diagnosis. In phase 1 (n = 49; 25 controls, 24 cancers), discovery total RNA sequencing was performed. Select exons underwent validation in phase 2 (n = 73; 35 controls, 29 cancers, 9 adenomas) using targeted capture sequencing (n = 10,371 probes). In phase 3 (n = 57; 30 controls, 27 cancers), RT-qPCR was performed on previously identified candidates (n = 99). There were 895 exons that were differentially expressed (325 upregulated, 570 downregulated) among cancers versus controls. In phases 2 and 3, fewer markers were validated than expected in independent sets of patients, most of which were from previously published literature (FGA, FGB, GPR107, CDH3, and RP23AP7). In summary, we optimized laboratory processes and data analysis strategies which can serve as methodological framework for future plasma RNA studies beyond just the scope of CRC detection. Additionally, further exploration is needed in order to determine if the few cfRNA candidates identified in this study have clinical utility for early CRC detection. Over time, advancements in technologies, data analysis, and RNA preservation methods at time of collection may improve the biological and technical reproducibility of cfRNA biomarkers and enhance the feasibility of RNA-based liquid biopsies.

Colorectal cancer (CRC) is the 2 nd most fatal cancer in the United States, but when detected early it is highly curable. Stool-derived extracellular vesicles (EVs) are a novel biomarker source that could augment the sensitivity for detection of CRC precursors. However, standardization of isolation methods for stool-derived EVs remains underexplored. We previously reported that size-exclusion chromatography (SEC) followed by ultrafiltration (UF-100kDa) was suitable for human stool supernatant EV isolation. In this study, we first assess alternative EV concentration methods (ultrafiltration [UF]; 10 kDa, 30 kDa, 50 kDa, 100 kDa and speed vacuum [SV]). Second, we investigate the host/bacterial EV proteomes by mass spectrometry. We report no difference in recovery, RNA and soluble protein contamination among concentration methods. Proteomic analysis reveals a diverse bacterial proteome, while human-derived proteins are more abundant. Specifically, pancreatic enzymes are among the most abundant proteins, further exploration revealed that zymogen granules are likely co-isolated in stool EV preparations. To enable discovery of EV-based molecular signatures of CRC precursors with high sensitivity, immunocapture strategies will likely be needed. Notably, we identified 10 surface proteins that may serve as candidates for the purification of colon-derived EVs. This work serves as framework for the future discovery and validation of EV-based biomarkers for CRC. This work uncovers the complex proteomic landscape of stool-derived extracellular vesicles (EVs). These findings serve as the framework for future stool EV biomarker discovery in gastrointestinal tract malignancies.

Embryo survival and pregnancy success is increased among animals that exhibit estrus prior to fixed time-artificial insemination, but there are no differences in conceptus survival to d16. The objective of this study was to determine effects of preovulatory estradiol on uterine transcriptomes, select trophectoderm (TE) transcripts, and uterine luminal fluid proteins. Beef cows/heifers were synchronized, artificially inseminated (d0), and grouped into either high (highE2) or low (lowE2) preovulatory estradiol. Uteri were flushed (d16); conceptuses and endometrial biopsies (n = 29) were collected. RNA sequencing was performed on endometrium. Real-time polymerase chain reaction (RT-PCR) was performed on TE (n = 21) RNA to measure relative abundance of IFNT, PTGS2, TM4SF1, C3, FGFR2, and GAPDH. Uterine fluid was analyzed using 2D Liquid Chromatography with tandem mass spectrometry-based Isobaric tags for relative and absolute quantitation (iTRAQ) method. RT-PCR data were analyzed using the MIXED procedure in SAS. There were no differences in messenger RNA (mRNA) abundances in TE, but there were 432 differentially expressed genes (253 downregulated, 179 upregulated) in highE2/conceptus versus lowE2/conceptus groups. There were also 48 differentially expressed proteins (19 upregulated, 29 downregulated); 6 of these were differentially expressed (FDR < 0.10) at the mRNA level. Similar pathways for mRNA and proteins included: calcium signaling, protein kinase A signaling, and corticotropin-releasing hormone signaling. These differences in uterine function may be preparing the conceptus for improved likelihood of survival after d16 among highE2 animals. Summary sentence Preovulatory estradiol did not impact conceptus survival to d16; however, it did influence uterine gene/protein expressions related to adhesion, endometrial remodeling, metabolism, and immune regulation, which may explain improved pregnancy success.

Identifying the genetic architecture of complex traits is important to many geneticists, including those interested in human disease, plant and animal breeding, and evolutionary genetics. Advances in sequencing technology and statistical methods for genome-wide association studies (GWAS) have allowed for the identification of more variants with smaller effect sizes, however, many of these identified polymorphisms fail to be replicated in subsequent studies. In addition to sampling variation, this failure to replicate reflects the complexities introduced by factors including environmental variation, genetic background, and differences in allele frequencies among populations. Using Drosophila melanogaster wing shape, we ask if we can replicate allelic effects of polymorphisms first identified in a GWAS (Pitchers et al. 2019) in three genes: dachsous (ds), extra-macrochaete (emc) and neuralized (neur), using artificial selection in the lab, and bulk segregant mapping in natural populations. We demonstrate that multivariate wing shape changes associated with these genes are aligned with major axes of phenotypic and genetic variation in natural populations. Following seven generations of artificial selection along the ds shape change vector, we observe genetic differentiation of variants in ds and genomic regions containing other genes in the hippo signaling pathway. This suggests a shared direction of effects within a developmental network. We also performed artificial selection with the emc shape change vector, which is not a part of the hippo signaling network, but showed a largely shared direction of effects. The response to selection along the emc vector was similar to that of ds, suggesting that the available genetic diversity of a population, summarized by the genetic (co)variance matrix (G), influenced alleles captured by selection. Despite the success with artificial selection, bulk segregant analysis using natural populations did not detect these same variants, likely due to the contribution of environmental variation and low minor allele frequencies, coupled with small effect sizes of the contributing variants.