Bioinformatic methodologies play a crucial role in the assessment of gut microbiota, offering advanced tools for analyzing complex microbial communities. These methodologies involve high-throughput sequencing technologies, such as 16S rRNA gene sequencing and metagenomics, which generate vast amounts of data on microbial diversity and functional potential, as well as whole-genome sequencing, which, while being more costly, has a more expansive potential. Bioinformatics tools and algorithms process these data to identify microbial taxa and quantify and elucidate their roles within the microbiome. Advanced statistical and computational models further enable the identification of microbiota patterns associated with various diseases and health conditions. Overall, bioinformatic approaches are essential for deciphering the complexities of gut microbiota so that, in the future, we may be able to discover treatments and technologies aimed at restoring or optimizing the microbiome. The goal of this review is to describe the differences in methodology and utilization of 16S versus whole-genome sequencing to address the increased understanding of the role that the gut microbiome plays in human physiology and pathology.

Background/Objectives: APOL1 renal-risk variants (RRVs) are of increasing relevance to kidney disease and transplant outcomes. It is currently understood that the presence of RRVs in donors negatively impacts kidney allograft survival in an autosomal recessive pattern of inheritance. Less well known is the interplay between ischemia and alternative allograft preservation methods, such as normothermic machine perfusion (NMP), on APOL1 gene expression. To investigate this, we examined the effects of APOL1 RRVs on APOL1 gene expression in ischemic donor kidneys and compared the differences in cytokine and APOL1 expression patterns between the alternative preservation methods, static cold storage (CS) and NMP. Methods: Non-utilized deceased donor kidney pairs from donors of African ancestry were procured from Mid-America Transplant after being deemed unsuitable for kidney transplant. Samples were collected from each donor kidney pair and DNA was extracted for APOL1 genotyping. APOL1 RRVs G1 (rs73885319) (rs60910145) and G2 (rs71785313) were identified by Sanger sequencing. From each pair, one kidney underwent 6 h NMP (n = 3) and the contralateral kidney 6 h of CS (n = 3) following the initial CS. Renal perfusion and biochemical, and histologic parameters were recorded. NMP was directly compared with CS using paired donor kidneys using NMP with allogeneic red blood cells, followed by assessment of perfusion, biochemical, and histologic parameters, in addition to gene expression. Results: Donor genotyping identified kidney pairs as heterozygous for the G1 RRV (G1/G0), homozygous for the G0 allele (G0/G0), and homozygous for the G2 RRV (G2/G2), respectively. All kidneys were successfully reperfused, with mRNA transcript levels of APOL1-related genes subsequently measured. Significant differences in APOL1 gene expression were observed among all three groups of kidneys. In paired kidneys from baseline to hour 6 of NMP, mRNA expression varied significantly between G1/G0 and G2/G2 homozygous pairs (p = 0.002) as well as between the G0/G0 and G2/G2 pairs (p = 0.002). APOL1 expression shifted by a significantly higher-fold change of 2.4 under NMP conditions in the G2/G2 genotype (p < 0.001). The inflammatory cytokine marker IFN-γ was also significantly upregulated in the G2/G2 genotype kidney, in both CS and NMP groups (p = 0.001). Other related genes such as KIM-1 were upregulated by a change of 3.9-fold in the NMP group for the G2/G2 kidney. Conclusion: Donor kidney pairs with the high-risk APOL1 genotype, especially G2/G2, show increased APOL1 expression and inflammation, particularly under NMP conditions. NMP enables detection of genotype-specific molecular changes in an ischemic reperfusion injury model, supporting its potential to improve donor kidney assessment before transplantation.