DNA fragmentation index (DFI), a new biomarker to diagnose male infertility, is closely associated with poor reproductive outcomes. Previous research reported that seminal microbiome correlated with sperm DNA integrity, suggesting that the microbiome may be one of the causes of DNA damage in sperm. However, it has not been elucidated how the microbiota exerts their effects. Here, we used a combination of 16S rRNA sequencing and untargeted metabolomics techniques to investigate the role of microbiota in high sperm DNA fragmentation index (HDFI). We report that increased specific microbial profiles contribute to high sperm DNA fragmentation, thus implicating the seminal microbiome as a new therapeutic target for HDFI patients. Additionally, we found that the amount of Lactobacillus species was altered: Lactobacillus iners was enriched in HDFI patients, shedding light on the potential influence of L. iners on male reproductive health. Finally, we also identified enrichment of the acetyl-CoA fermentation to butanoate II and purine nucleobase degradation I in the high sperm DNA fragmentation samples, suggesting that butanoate may be the target metabolite of sperm DNA damage. These findings provide valuable insights into the complex interplay between microbiota and sperm quality in HDFI patients, laying the foundation for further research and potential clinical interventions.IMPORTANCEThe DNA fragmentation index (DFI) is a measure of sperm DNA fragmentation. Because high sperm DNA fragmentation index (HDFI) has been strongly associated with adverse reproductive outcomes, this has been linked to the seminal microbiome. Because the number of current treatments for HDFI is limited and most of them have no clear efficacy, it is critical to understand how semen microbiome exerts their effects on sperm DNA. Here, we evaluated the semen microbiome and its metabolites in patients with high and low sperm DNA fragmentation. We found that increased specific microbial profiles contribute to high sperm DNA fragmentation. In particular, Lactobacillus iners was uniquely correlated with high sperm DNA fragmentation. Additionally, butanoate may be the target metabolite produced by the microbiome to damage sperm DNA. Our findings support the interaction between semen microbiome and sperm DNA damage and suggest that seminal microbiome should be a new therapeutic target for HDFI patients.

The tumor suppressor p14/19ARF regulates ribosomal RNA (rRNA) synthesis by controlling the nucleolar localization of Transcription Termination Factor 1 (TTF1). However, the role played by TTF1 in regulating the rRNA genes and in potentially controlling growth has remained unclear. We now show that TTF1 expression regulates cell growth by determining the cellular complement of ribosomes. Unexpectedly, it achieves this by acting as a \"roadblock\" to synthesis of the noncoding LncRNA and pRNA that we show are generated from the \"Spacer Promoter\" duplications present upstream of the 47S pre-rRNA promoter on the mouse and human ribosomal RNA genes. Unexpectedly, the endogenous generation of these noncoding RNAs does not induce CpG methylation or gene silencing. Rather, it acts in cis to suppress 47S preinitiation complex formation and hence de novo pre-rRNA synthesis by a mechanism reminiscent of promoter interference or occlusion. Taken together, our data delineate a pathway from p19ARF to cell growth suppression via the regulation of ribosome biogenesis by noncoding RNAs and validate a key cellular growth law in mammalian cells.

While DNA methylation and gastric microbiome are each associated with gastric cancer (GC), their combined role in predicting GC remains unclear. This study investigated the potential of a combined DNA methylation and gastric microbiome signature to predict Helicobacter pylori-negative GC.
In this case-control study, we conducted quantitative methylation-specific polymerase chain reaction to measure the methylation levels of DKK3, SFRP1, EMX1, NKX6-1, MIR124-3, and TWIST1 in the gastric mucosa from 75 H. pylori-negative patients, including chronic gastritis (CG), intestinal metaplasia (IM), and GC. A combined analysis of DNA methylation and gastric microbiome, using 16S rRNA gene sequencing, was performed in 30 of 75 patients.
The methylation levels of DKK3, SFRP1, EMX1, MIR124-3, and TWIST1 were significantly higher in patients with GC than in controls (all q<0.05). MIR124-3 and TWIST1 methylation levels were higher in patients with IM than those with CG and also in those with GC than in those with IM (all q<0.05). A higher methylation level of TWIST1 was an independent predictor for H. pylori-negative GC after adjusting for age, sex, and atrophy (odds ratio [OR], 15.15; 95% confidence interval [CI], 1.58 to 145.46; p=0.018). The combination of TWIST1 methylation and GC microbiome index (a microbiome marker) was significantly associated with H. pylori-negative GC after adjusting for age, sex, and atrophy (OR, 50.00; 95% CI, 1.69 to 1,476; p=0.024).
The combination of TWIST1 methylation and GC microbiome index may offer potential as a biomarker for predicting H. pylori-negative GC.

BACKGROUND: One of the stranger phenomena that can occur during gene translation is where, as a ribosome reads along the mRNA, various cellular and molecular properties contribute to stalling the ribosome on a slippery sequence and shifting the ribosome into one of the other two alternate reading frames. The alternate frame has different codons, so different amino acids are added to the peptide chain. More importantly, the original stop codon is no longer in-frame, so the ribosome can bypass the stop codon and continue to translate the codons past it. This produces a longer version of the protein, a fusion of the original in-frame amino acids, followed by all the alternate frame amino acids. There is currently no automated software to predict the occurrence of these programmed ribosomal frameshifts (PRF), and they are currently only identified by manual curation.
RESULTS: Here we present PRFect, an innovative machine-learning method for the detection and prediction of PRFs in coding genes of various types. PRFect combines advanced machine learning techniques with the integration of multiple complex cellular properties, such as secondary structure, codon usage, ribosomal binding site interference, direction, and slippery site motif. Calculating and incorporating these diverse properties posed significant challenges, but through extensive research and development, we have achieved a user-friendly approach. The code for PRFect is freely available, open-source, and can be easily installed via a single command in the terminal. Our comprehensive evaluations on diverse organisms, including bacteria, archaea, and phages, demonstrate PRFect\'s strong performance, achieving high sensitivity, specificity, and an accuracy exceeding 90%. The code for PRFect is freely available and installs with a single terminal command.
CONCLUSIONS: PRFect represents a significant advancement in the field of PRF detection and prediction, offering a powerful tool for researchers and scientists to unravel the intricacies of programmed ribosomal frameshifting in coding genes.

An 84-year-old man in Japan who had undergone endovascular aortic repair 9 years earlier had an infected aneurysm develop. We detected Desulfovibrio desulfuricans MB at the site. The patient recovered after surgical debridement, artificial vessel replacement, and appropriate antimicrobial therapy. Clinicians should suspect Desulfovibrio spp. infection in similar cases.

Lipopeptides are surface active, natural products of bacteria, fungi and green-blue algae origin, having diverse structures and functionalities. In analogy, a number of chemical synthesis techniques generated new designer lipopeptides with desirable features and functions. Lipopetides are self-assembly guided, supramolecular compounds which have the capacity of high-density presentation of the functional epitopes at the surface of the nanostructures. This feature contributes to their successful application in several industry sectors, including food, feed, personal care, and pharmaceutics. In this comprehensive review, the novel class of ribosomally synthesized lipopeptides is introduced alongside the more commonly occuring non-ribosomal lipopeptides. We highlight key representatives of the most researched as well as recently described lipopeptide families, with emphasis on structural features, self-assembly and associated functions. The common biological, chemical and hybrid production routes of lipopeptides, including prominent analogues and derivatives are also discussed. Furthermore, genetic engineering strategies aimed at increasing lipopeptide yields, diversity and biological activity are summarized and exemplified. With respect to application, this work mainly details the potential of lipopeptides in personal care and cosmetics industry as cleansing agents, moisturizer, anti-aging/anti-wrinkling, skin whitening and preservative agents as well as the pharmaceutical industry as anitimicrobial agents, vaccines, immunotherapy, and cancer drugs. Given that this review addresses human applications, we conclude on the topic of safety of lipopeptide formulations and their sustainable production.

UNASSIGNED: One of the stranger phenomena that can occur during gene translation is where, as a ribosome reads along the mRNA, various cellular and molecular properties contribute to stalling the ribosome on a slippery sequence, shifting the ribosome into one of the other two alternate reading frames. The alternate frame has different codons, so different amino acids are added to the peptide chain, but more importantly, the original stop codon is no longer in-frame, so the ribosome can bypass the stop codon and continue to translate the codons past it. This produces a longer version of the protein, a fusion of the original in-frame amino acids, followed by all the alternate frame amino acids. There is currently no automated software to predict the occurrence of these programmed ribosomal frameshifts (PRF), and they are currently only identified by manual curation.
UNASSIGNED: Here we present PRFect, an innovative machine-learning method for the detection and prediction of PRFs in coding genes of various types. PRFect combines advanced machine learning techniques with the integration of multiple complex cellular properties, such as secondary structure, codon usage, ribosomal binding site interference, direction, and slippery site motif. Calculating and incorporating these diverse properties posed significant challenges, but through extensive research and development, we have achieved a user-friendly approach. The code for PRFect is freely available, open-source, and can be easily installed via a single command in the terminal. Our comprehensive evaluations on diverse organisms, including bacteria, archaea, and phages, demonstrate PRFect\'s strong performance, achieving high sensitivity, specificity, and an accuracy exceeding 90%.
UNASSIGNED: PRFect represents a significant advancement in the field of PRF detection and prediction, offering a powerful tool for researchers and scientists to unravel the intricacies of programmed ribosomal frameshifting in coding genes.

Stroke is a common group of cerebrovascular diseases that can lead to brain damage or death. Several studies have shown a close link between oral health and stroke. However, the oral microbiome profiling of ischemic stroke (IS) and its potential clinical implication are unclear. This study aimed to describe the oral microbiota composition of IS, the high risk of IS, and healthy individuals and to profile the relationship between microbiota and IS prognosis.
This observational study recruited three groups: IS, high-risk IS (HRIS), and healthy control (HC) individuals. Clinical data and saliva were collected from participants. The modified Rankin scale score after 90 days was used to assess the prognosis of stroke. Extracted DNA from saliva and performed 16S ribosomal ribonucleic acid (rRNA) gene amplicon sequencing. Sequence data were analyzed using QIIME2 and R packages to evaluate the association between the oral microbiome and stroke.
A total of 146 subjects were enrolled in this study according to the inclusion criteria. Compared with HC, HRIS and IS demonstrated a progressive increase trend in Chao1, observed species richness, and Shannon and Simpson diversity index. On the basis of permutational multivariate analysis of variance, the data indicate a great variation in the saliva microbiota composition between HC and HRIS (F = 2.40, P < 0.001), HC and IS (F = 5.07, P < 0.001), and HRIS and IS (F = 2.79, P < 0.001). The relative abundance of g_Streptococcus, g_Prevotella, g_Veillonella, g_Fusobacterium, and g_Treponema was higher in HRIS and IS compared with that in HC. Furthermore, we constructed the predictive model by differential genera to effectively distinguish patients with IS with poor 90-day prognoses from those with good (area under the curve = 79.7%; 95% CI, 64.41%-94.97%; p < 0.01).
In summary, the oral salivary microbiome of HRIS and IS subjects have a higher diversity, and the differential bacteria have some predictive value for the severity and prognosis of IS. Oral microbiota may be used as potential biomarkers in patients with IS.

Basic knowledge on the biology and epidemiology of equine strongylid species still needs to be improved to contribute to the design of better parasite control strategies. Nemabiome metabarcoding is a convenient tool to quantify and identify species in bulk samples that could overcome the hurdle that cyathostomin morphological identification represents. To date, this approach has relied on the internal transcribed spacer 2 (ITS-2) of the ribosomal RNA gene, with a limited investigation of its predictive performance for cyathostomin communities. Using DNA pools of single cyathostomin worms, this study aimed to provide the first elements to compare performances of the ITS-2 and a cytochrome c oxidase subunit I (COI) barcode newly developed in this study. Barcode predictive abilities were compared across various mock community compositions of two, five and 11 individuals from distinct species. The amplification bias of each barcode was estimated. Results were also compared between various types of biological samples, i.e., eggs, infective larvae or adults. Bioinformatic parameters were chosen to yield the closest representation of the cyathostomin community for each barcode, underscoring the need for communities of known composition for metabarcoding purposes. Overall, the proposed COI barcode was suboptimal relative to the ITS-2 rDNA region, because of PCR amplification biases, reduced sensitivity and higher divergence from the expected community composition. Metabarcoding yielded consistent community composition across the three sample types. However, imperfect correlations were found between relative abundances from infective larvae and other life-stages for Cylicostephanus species using the ITS-2 barcode. While the results remain limited by the considered biological material, they suggest that additional improvements are needed for both the ITS-2 and COI barcodes.

Interstitial cystitis/bladder pain syndrome is a chronic urological condition diagnosed in nearly 8 million females in the United States. Whether urinary microbiota play an etiological role remains controversial. Most studies assessed the microbiota of interstitial cystitis/bladder pain syndrome patients with voided or catheterized urine as a proxy for bladder urothelium; however, urine may not be a true reflection of the bladder microbiota. Bladder biopsy tissue may provide a more accurate, and thus more clinically relevant, picture of bladder microbiota.
Bladder biopsy tissues were obtained from: (1) 30 females with interstitial cystitis/bladder pain syndrome (18-80 years old) via cystoscopically guided cold-cup biopsy following therapeutic bladder hydrodistention, and (2) 10 non-interstitial cystitis/bladder pain syndrome females undergoing pelvic organ prolapse repair. To detect bacteria, technical duplicates of each RNAlater-preserved biopsy were subjected to 16S rRNA gene sequencing. To visualize bacteria, paraformaldehyde-fixed, paraffin-embedded biopsies were subjected to a combined multiplexed fluorescence in situ hybridization and fluorescence immunohistochemistry assay and confocal microscopy.
Bacteria were detected by 16S rRNA gene sequencing in at least 1 technical duplicate of most biopsies. The most abundant genus was Staphylococcus, followed by Lactobacillus; Escherichia was common but not abundant. There was no significant difference between interstitial cystitis/bladder pain syndrome patients and controls (P > .05). Combined fluorescence in situ hybridization and immunohistochemistry reproducibly detected 16S rRNA in epithelial cells and shed cells in the urothelium and lesioned areas and capillary walls in the lamina propria of human bladder biopsy tissue.
We conclude that urothelial and urinary microbiota are similar but not identical in adult females.