Overcoming barriers to early disease intervention

Caicedo, H. H.; Hashimoto, Daniel A.; Caicedo, J.C.; Pentland, Alex; Pisano, Gary P.

doi:10.1038/s41587-020-0550-z

Cited by 96 publications

(38 citation statements)

References 13 publications

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“…In addition, we predicted the metabolic profiles of microbiomes using the novel bioinformatics tool PICRUSt2, which enabled us to investigate the functional traits of the microbiome under disease pressure. PICRUSt2 is more accurate than other metagenome predictive algorithms as it uses all surveyed 16s ASVs (through sequence alignment) in a vast catalog of reference metagenomes (Douglas et al, 2020). The algorithm was updated with the new denoising methods (i.e., DADA2), thus enabling sequence analysis resolution down to the single-nucleotide level and enabling the differentiation of closely related organisms and more precise 16S sequence gene annotations (Douglas et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…In addition, the 16S ASVs data sets were used to predict metagenome functional content in each microbiome. The metagenome predictions were performed with the bioinformatics software package PICRUSt2 (Douglas et al, 2020). Briefly, the 16S ASVs were aligned (NSTI cutoff value of 2) to a reference phylogenetic tree containing more than 20,000 16S sequence variants from prokaryotes; from here, the software predicted functional gene families and copy numbers for each specific ASV.…”

Section: Bioinformatic Analysis Of Amplicon Sequencesmentioning

confidence: 99%

“…To assess the impact of microbial taxa modulation by C. parvum on the functional profiles of goat gut microbiomes, we performed pathway profiling based on predicted metagenomic functions using the bioinformatic tool PICRUSt2 (Douglas et al, 2020). A total of 387 pathways were identified in all the samples.…”

Section: Microbiota Modulation By C Parvum Affects the Functional Prmentioning

confidence: 99%

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Cryptosporidium parvum Infection Depletes Butyrate Producer Bacteria in Goat Kid Microbiome

et al. 2020

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Cryptosporidium parvum is an important apicomplexan parasite infecting ruminants and humans. We characterized the impact of C. parvum infection on the goat kid microbiome. C. parvum was orally administered to parasite-naïve goats, and infection was monitored for 26 days in fecal samples using immunofluorescence assay and qPCR tests. Age-matched goats served as uninfected controls. A reduction in body weight gain, diarrhea, and dehydration were observed in infected goats compared to the uninfected controls. Infection decreased the bacterial diversity 5 days post-infection (dpi), but this parameter recovered at 15 dpi. The infection altered the relative abundance of several taxa. A total of 38 taxa displayed significant differences in abundance between control and infected goats at both 5 and 15 dpi. Co-occurrence network analysis revealed that the infection resulted in a differential pattern of taxa interactions and that C. parvum infection increased the relative abundance of specific taxa. The 16S data set was used for metagenome predictions using the software package PICRUSt2. As many as 34 and 40 MetaCyc pathways (from 387 total) were significantly affected by the infection at 5 and 15 dpi, respectively. Notably, C. parvum decreased the abundance of butyrate-producing pathways in bacteria. Low levels of butyrate may increase mucosal inflammation and tissue repair. Our results suggest that the gut inflammation induced by C. parvum infection is associated with the reduction of butyrate-producing bacteria. This insight could be the basis for the development of novel control strategies to improve animal health.

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Section: Discussionmentioning

confidence: 99%

Section: Bioinformatic Analysis Of Amplicon Sequencesmentioning

confidence: 99%

Section: Microbiota Modulation By C Parvum Affects the Functional Prmentioning

confidence: 99%

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Cryptosporidium parvum Infection Depletes Butyrate Producer Bacteria in Goat Kid Microbiome

et al. 2020

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“…The functional profiles of the microbial communities based on 16S rRNA gene sequences were predicted using the latest version of PICRUSt2 (v2.3.0‐b) according to the KEGG Orthology (Caicedo et al., 2020). Heatmaps of KEGG level 1 and level 2 pathways and the digestion‐related genes were plotted using the “pheatmap” package in R. The digestion‐related genes were selected based on a study of the gut microbiomes of the blunt snout bream (Wei et al., 2018).…”

Section: Methodsmentioning

confidence: 99%

Diversity of gut microbiomes in marine fishes is shaped by host‐related factors

et al. 2020

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“…A total of 481 CM patients with clinical profiles, among which 475 CM patients with available RNA sequence data downloaded from UCXC ( https://xenabrowser.net/datapages/ ) [ 29 ], were consecutively recruited in analyses. Phenotype and transcriptional expression profiles in 481 melanoma patients from TCGA were analyzed and displayed.…”

Section: Methodsmentioning

confidence: 99%

Identification, Validation, and Functional Annotations of Genome-Wide Profile Variation between Melanocytic Nevus and Malignant Melanoma

Han

Wang

et al. 2020

BioMed Research International

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Cutaneous melanoma (CM) is known as an aggressive malignant cancer; some of which are directly derived from melanocytic nevi, which have been attracting growing attention from the last decades. This study focused on comprehensive identification, validation, and functional annotations of prognostic differentially expressed genes (DEGs) between melanocytic nevus and malignant melanoma in genome-wide profiles. DEGs were obtained using three chip datasets from GEO database to identify after standardization annotation. A total of 73 DEGs were identified as possible candidate prognostic biomarkers between melanocytic nevus and malignant melanoma. In addition, survival curves indicated that six hub genes, including FABP5, IVL, KRT6A, KRT15, KRT16, and TIMP2, were significant prognostic signatures for CM and of significant value to predict transformation from nevi to melanoma. Furthermore, immunohistochemistry staining was performed to validate differential expression levels and prognostic implications of six hub genes between CM tissue and nevus tissues from the First Affiliated Hospital of Soochow University cohort. It suggested that significantly elevated FABP5, IVL, KRT6A, KRT15, KRT16, and TIMP2 proteins expressed in the CM than in the nevus tissues. Functional enrichment and significant pathways of the six significant hub genes indicated that the mostly involved hallmarks include the P53 pathway, K-ras signaling, estrogen response late, and estrogen response early. In summary, this study identified significant DEGs participating in the process of malignant transformation from nevus to melanoma tissues based on comprehensive genomic profiles. Transcription profiles of FABP5, IVL, KRT6A, KRT15, KRT16, and TIMP2 provided clues of prognostic implications, which might help us evaluate malignant potential of nevus and underlying carcinogenesis progress from melanocytic nevus to melanoma.

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Overcoming barriers to early disease intervention

Cited by 96 publications

References 13 publications

Cryptosporidium parvum Infection Depletes Butyrate Producer Bacteria in Goat Kid Microbiome

Cryptosporidium parvum Infection Depletes Butyrate Producer Bacteria in Goat Kid Microbiome

Diversity of gut microbiomes in marine fishes is shaped by host‐related factors

Identification, Validation, and Functional Annotations of Genome-Wide Profile Variation between Melanocytic Nevus and Malignant Melanoma

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