CleanSeqU algorithm for decontamination of catheterized urine 16S rRNA sequencing data

Accurately quantifying microbial abundance from high-throughput sequencing data is challenging, especially in low-biomass samples where host DNA/RNA dominates microbial content. Host or environmental contaminants may obscure true microbial signals, leading to false positives. Here, we introduce MicroHunt, an advanced pipeline integrating quality control, host sequence depletion, microbial classification, and contaminant exclusion.MicroHunt incorporates comprehensive human reference genomes (hg38, T2T-CHM13, Gencode) to efficiently remove host-derived reads and eliminates contaminant sequences source, such as vectors, phages, and plasmids. It supports multiple microbial classification tools and utilizes a curated reference database encompassing archaea, fungi, bacteria, viruses, and protozoa. By incorporating host genome references into the classification process, MicroHunt clearly distinguishes host from microbial sequences, significantly improving classification accuracy and reducing false positives. MicroHunt also provides integrated contaminant control strategies effective even without negative controls, enabling reliable microbial quantification from low-biomass samples. Using ribosomal RNA-depleted whole-transcriptome sequencing data from 807 colorectal cancer (CRC) tumor samples in the AVANT Phase III trial, MicroHunt effectively characterized the dominant microbial phyla present within the tumor microbiome of CRC patients, with Pseudomonadota and Bacillota being the most prevalent. Further analysis revealed that CRC patients with high abundance of Lactobacillus iners (L. iners) in tumor tissues were significantly associated with poor prognosis following chemotherapy combined with bevacizumab treatment (Hazard Ratio = 2.21, 95% CI = 1.14-4.32, p = 0.017). Sequence alignment analysis confirmed that the reads identified as L. iners were not derived from potential contamination sources. Moreover, integrating microbiome data generated by MicroHunt with patient transcriptomic data uncovered complex interactions between the gut microbiome and host gene expression in CRC patients. Pathway enrichment analysis revealed a significant association between L. iners and the fatty acid oxidation pathway (Spearman’s correlation coefficient r = 0.094, p = 0.0079), suggesting that microbial metabolism may influence patient prognosis in CRC. Finally, we validated the utility of MicroHunt using sequencing data from other tumor types, including non-small cell lung cancer and bladder cancer, successfully identifying intratumoral microbes and elucidating their potential biological significance. Citation Format: Gengwen Deng, Lingxuan Zhu, Weiming Mou, Liling Xu, Shujia Lin, Keren Wu, Hao Li, Zhixing Deng, Hongsen Huang, Zeji Guo, Qiheng Liang, Aimin Jiang, TIng Wei, Jiang Zhang, Quan Cheng, Anqi Lin, Peng Luo. Microhunt: an integrated pipeline for precise microbial quantification in low-biomass clinical samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2506.

The aim was to evaluate the effect of type 2 diabetes mellitus on the root canal microbiota and its response to antimicrobial photodynamic therapy (aPDT) combined with chemomechanical preparation in asymptomatic apical periodontitis (AP), by next-generation sequencing. A total of 22 teeth with a single root and single canal, diagnosed with asymptomatic AP, were included in this study: 11 teeth from patients with T2D (T2D group) and 11 from systemically healthy individuals (Control group). Root canal samples were collected before root canal treatment and after aPDT combined with chemomechanical preparation. Following chemomechanical preparation, canals were incubated with methylene blue for 5 min and photoactivated with a 630 nm LED for 60 s. Root canal samples were collected at two time points—before treatment (Control.Pre, T2D.Pre) and after treatment (Control.aPDT, T2D.aPDT). Following propidium monoazide (PMA) treatment, genomic DNA was isolated using a silica column method and quantified fluorometrically. The V3–V4 regions of the 16S rRNA gene were amplified and sequenced using the Illumina MiSeq platform. Data were processed in QIIME2 with DADA2 for denoising and classified taxonomically using Human Oral Microbiome Database (HOMD). Diversity analyses and statistical evaluations (PERMANOVA and multivariable association analysis using MaAsLin3; FDR-corrected) were performed in R. A total of 44 root canal samples (Control.Pre, Control.aPDT, T2D.Pre, T2D.aPDT; n = 11) were analyzed via 16S rRNA V3–V4 sequencing, yielding 4.6 million high-quality reads and 2,745 Amplicon Sequence Variants (ASVs). Alpha diversity did not differ between pre and post disinfection procedure samples in healthy individuals (p > 0.05), whereas a significant reduction in observed ASV richness was detected in the T2D group after the disinfection procedures (p < 0.05). The number of ASVs shared between pre and post disinfection procedure samples was lower in the T2D group than in controls. Beta diversity based on unweighted UniFrac distances showed significant shifts after the disinfection procedures in both groups (p < 0.05), while weighted UniFrac analyses showed no significant differences (p > 0.05). Taxonomic analysis revealed a post disinfection increase in oxygen tolerant taxa and a reduction in obligate anaerobes in both groups, with more pronounced changes in the T2D group. Following chemomechanical preparation and aPDT, a pronounced restructuring of the root canal microbiota was observed in both healthy individuals and individuals with T2D. In individuals with T2D, the post-disinfection period was characterized by reduced alpha diversity and a lower number of shared ASVs, indicating more limited microbial continuity. The reduced microbial stability observed in individuals with diabetes suggests that systemic metabolic status may affect microbial responses to chemomechanical disinfection combined with aPDT.

940: Comparison of placenta with DNA extraction controls provides evidence for distinct microbiota in placenta samples

Microbiome studies in animal science using 16S rRNA gene sequencing have become increasingly common in recent years as sequencing costs continue to fall and bioinformatic tools become more powerful and user-friendly. The combination of molecular biology, microbiology, microbial ecology, computer science, and bioinformatics—in addition to the traditional considerations when conducting an animal science study—makes microbiome studies sometimes intimidating due to the intersection of different fields. The objective of this review is to serve as a jumping-off point for those animal scientists less familiar with 16S rRNA gene sequencing and analyses and to bring up common issues and concerns that arise when planning an animal microbiome study from design through analysis. This review includes an overview of 16S rRNA gene sequencing, its advantages, and its limitations; experimental design considerations such as study design, sample size, sample pooling, and sample locations; wet lab considerations such as field handing, microbial cell lysis, low biomass samples, library preparation, and sequencing controls; and computational considerations such as identification of contamination, accounting for uneven sequencing depth, constructing diversity metrics, assigning taxonomy, differential abundance testing, and, finally, data availability. In addition to general considerations, we highlight some special considerations by species and sample type.

Reagent-derived contamination can compromise the integrity of microbiome data, particularly in low microbial biomass samples. This contamination has recently been attributed to the 'kitome' (contamination introduced by the DNA extraction kit), prior to which attention was mostly paid to potential contamination introduced by PCR reagents. In this study, we assessed the proportion to which our DNA extraction kit and PCR master mix introduce contaminating microbial DNA to bacterial microbial profiles generated by 16S rRNA gene sequencing. Utilizing a commercial dsDNase treatment protocol to decontaminate the PCR master mix, we demonstrated that the vast majority of contaminating DNA was derived from the PCR master mix. Importantly, this contamination was almost completely eliminated using the simple dsDNase treatment, resulting in a 99% reduction in contaminating bacterial reads. We suggest that dsDNase treatment of PCR reagents should be explored as a simple and effective way of reducing contamination in low-biomass microbiome studies and producing more robust and reliable data. SIGNIFICANCE AND IMPACT OF THE STUDY: Reagent contamination with microbial DNA is a major problem in microbiome studies of low microbial biomass samples. Levels of such contaminating DNA often outweigh what is present in the sample and heavily confound subsequent data analysis. Previous studies have suggested this contamination is primarily derived from DNA extraction kits. Here, we identified the PCR master mix as the primary source of contamination, and showed that enzymatic removal of the contamination drastically reduced the blank signal and improved precision. Decontamination of PCR master mixes may have the potential to improve the sensitivity and accuracy of low-biomass microbiome studies.

Endometrial cancer (EC) is the most common gynaecological malignancy globally, with rising incidence and notable disparities in outcomes. In New Zealand, EC rates have increased significantly, particularly among Māori and Pacific women, who face higher risks of advanced disease and poorer outcomes. Microbial dysbiosis has been implicated in EC pathogenesis, but characterising the uterine microbiome is challenging due to low microbial biomass and high contamination risk. This study aimed to pilot a protocol that could inform the preparation of a larger cohort trial. Short-read Illumina MiSeq and long-read Oxford Nanopore Technologies (ONT) 16S rRNA gene sequencing were investigated to profile the uterine microbiome in people with EC. Uterine and vaginal swabs were analysed to assess platform performance in terms of DNA recovery, sequencing success, diversity metrics, and taxonomic resolution. The impact of sample freezing or immediate lysis prior to DNA extraction was also evaluated. ONT sequencing provided enhanced species-level resolution and improved detection of low-abundance taxa but showed variable performance in low-yield samples. Freezing prior to cell DNA extraction modestly increased bacterial 16S copy numbers and improved community consistency. Contamination was a problem across both platforms, particularly in low-biomass samples, but can be minimised during data analysis. This study provides practical guidance for sequencing platform selection and sample handling in uterine microbiome research. Our findings support future efforts to elucidate microbial contributions to EC pathogenesis and highlight the importance of rigorous contamination control. Importantly, this is the first presentation of a New Zealand cohort and contributes valuable data from an underrepresented population and informs future research in diverse clinical settings.

Microbial sequences inferred as belonging to one sample may not have originated from that sample. Such contamination may arise from laboratory or reagent sources or from physical exchange between samples. This study seeks to rigorously assess the behavior of this often-neglected between-sample contamination. Using unique bacteria, each assigned a particular well in a plate, we assess the frequency at which sequences from each source appear in other wells. We evaluate the effects of different DNA extraction methods performed in two laboratories using a consistent plate layout, including blanks and low-biomass and high-biomass samples. Well-to-well contamination occurred primarily during DNA extraction and, to a lesser extent, in library preparation, while barcode leakage was negligible. Laboratories differed in the levels of contamination. Extraction methods differed in their occurrences and levels of well-to-well contamination, with plate methods having more well-to-well contamination and single-tube methods having higher levels of background contaminants. Well-to-well contamination occurred primarily in neighboring samples, with rare events up to 10 wells apart. This effect was greatest in samples with lower biomass and negatively impacted metrics of alpha and beta diversity. Our work emphasizes that sample contamination is a combination of cross talk from nearby wells and background contaminants. To reduce well-to-well effects, samples should be randomized across plates, samples of similar biomasses should be processed together, and manual single-tube extractions or hybrid plate-based cleanups should be employed. Researchers should avoid simplistic removals of taxa or operational taxonomic units (OTUs) appearing in negative controls, as many will be microbes from other samples rather than reagent contaminants.IMPORTANCE Microbiome research has uncovered magnificent biological and chemical stories across nearly all areas of life science, at times creating controversy when findings reveal fantastic descriptions of microbes living and even thriving in what were once thought to be sterile environments. Scientists have refuted many of these claims because of contamination, which has led to robust requirements, including the use of controls, for validating accurate portrayals of microbial communities. In this study, we describe a previously undocumented form of contamination, well-to-well contamination, and show that this sort of contamination primarily occurs during DNA extraction rather than PCR, is highest with plate-based methods compared to single-tube extraction, and occurs at a higher frequency in low-biomass samples. This finding has profound importance in the field, as many current techniques to "decontaminate" a data set simply rely on an assumption that microbial reads found in blanks are contaminants from "outside," namely, the reagents or consumables.

Capsicum chlorosis virus (CaCV) is a negative sense ssRNA virus belonging to the genus Orthotospovirus in the family Tospoviridae. It was first discovered in Australia, and then reported in other places including Thailand, China, India, Greece, and United States (Zheng et al.2011; Melzer et al.2014; Chrysoula et al. 2018; Abudurexiti et al. 2019). CaCV infects plants of the families Amaranthaceae, Apocynaceae, Chenopodiaceae, Cucurbitaceae, Amaryllidaceae, Fabaceae and Solanaceae (Basavaraj et al. 2017; Basavaraj et al. 2020). Chromolaena odorata L. (commonly known as Feiji cao in China) is an invasive weedy herb that belongs to the genus Eupatorium (family Asteraceae), and is native to Central America. In May 2020, serrated chlorotic ring and chlorotic ringspots resembling symptoms of orthotospovirus infection (Supplementary Figure 1) was observed on the leaves of C. odorata plants in Honghe County, Yunnan. Three symptomatic leaf samples were collected and double antibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA) was performed using antisera targeting Tomato spotted wilt virus (TSWV), Calla lily chlorotic spot virus (CCSV), Capsicum chlorosis virus (CaCV), and Tomato zonate spot virus (TZSV) (Proteintech Group, Inc., China). Buffer solution and healthy leaves were used as a blank and negative controls, respectively. All three symptomatic samples showed positive reactions with only CaCV antiserum (OD450 of 0.315-0.345 relative to 0.078 and 0.076 for healthy plants and the blank control, respectively. The total RNA extracted from the positive samples were further analyzed by reverse transcription-polymerase chain reaction (RT-PCR) using generic primers gL3637 (CCTTTAACAGTDGAAACAT) and gL4435c (CATDGCRCAAGARTGRTARACAGA) which were designed to amplify partial L segment encoding the RNA-dependent RNA polymerase (RdRP) of orthotospoviruses (Chu, et al. 2001). The expected ~800 bp DNA fragment was amplified from all three positive samples by RT-PCR. The amplified DNA was cloned and sequenced. BLAST search of the partial L RNA sequence (GenBank acc. nos. MW964378 to MW964380) revealed that they shared 86.2-97.4% nucleotide (nt) and 97.2-100% amino acid (aa) sequence identities with different isolates of CaCV available in GenBank with CaCV chili isolates (KU941834 to KU941836) from India sharing the highest aa identity of 100%. This confirmed the presence of CaCV in the symptomatic C. odorata plants. The 825 bp complete nucleocapsid protein (NP) of CaCV was also amplified from the samples using primers CaCV-F: ATGTCTAMCGTYAGGCAAC and CaCV-R: TYACACYTCWATAGAWGTACTAG) (Basavaraj et al. 2020), cloned, and sequenced to obtain complete S fragment-nucleocapsid protein (NP) with a size of 825 bp (MW964381 to MW964383). The pairwise comparisons of three fragments showed 85.1-98.3% nt and 87.6-99.6% aa sequence identities with different isolates of CaCV. Maximum-Likelihood phylogenetic trees inferred from the partial RdRP and complete NP aa sequences showed that the C. odorata isolates (CaCV-YN) clustered closely with CaCV tomato isolate from Taiwan and tomato (Yuxi-2013) isolate from China, respectively (Supplementary Figure 1). To our knowledge, this is the first time CaCV has been detected in C. odorata. This study will serve as an important reference for the study of host range of CaCV. Further studies will be required to determine whether thrips could transmit CaCV between C. odorata and other hosts of the virus.

The environmental impact of microbial pesticides, including Bacillus thuringiensis (Bt), is a growing concern. Although Bt is widely used for pest control due to its efficacy, understanding its potential toxicity to non-target organisms such as silkworms is essential for environmental safety. The current study was conducted to determine how different Bt doses affect larval mortality, growth, and development of silkworm (Bombyx mori) larvae. The study was conducted at Group of Pesticide environmental risk assessment and control, Institute of Plant Protection, Chinese Academy of Agricultural Sciences (IPPCAAS), between 2019 and 2020. This study investigated the dose-dependent toxicity of Bt to silkworms following the NY/T 3152.3-2017 guidelines for microbial pesticide risk assessment. A dose-response experiment was conducted using five Bt concentrations (3.16 × 10⁴, 1 × 10⁵, 3.16 × 10⁵, 1 × 10⁶, and 3.16 × 10⁶ CFU/mL), along with blank and inactivated controls. Each treatment consisted of 20 silkworms with four replicates, and the experiment lasted 23 days. The effects of Bt on silkworm survival and development were evaluated using Probit analysis and one-way ANOVA. The result revealed that the 23-day LC₅₀ was 4.48 × 10⁵ CFU/mL (95% confidence interval: 2.77 × 10⁵- 6.06 × 10⁵ CFU/mL). At 1.00 × 10⁶ CFU/mL, cocoon weight was significantly higher than in the blank control, though no significant differences were observed among other groups. Cocoon shell weight was significantly higher at 3.16 × 10⁴ and 1 × 10⁶ CFU/mL compared to the control. Pathogenicity tests confirmed that the isolated and tested strains were identical, and infected silkworms exhibited typical Bt-induced symptoms, including body decay and side-lying behavior. Overall, these findings provide important data for environmental risk assessment, indicating that careful management of Bt concentrations is critical to minimize unintended harm to beneficial organisms within agricultural ecosystems.

Production and enhanced biological activity of a novel GHRH analog, hGHRH with an N-terminal Pro–Pro extension

The regulatory role of Annexin 3 in a nude mouse bearing a subcutaneous xenograft of MDA-MB-231 human breast carcinoma

SummaryTo quantify the major environmental drivers of stream bacterial population dynamics, we modelled temporal differences in stream bacterial communities to quantify community shifts, including those relating to cyclical seasonal variation and more sporadic bloom events. We applied Illumina MiSeq 16S rRNA bacterial gene sequencing of 892 stream biofilm samples, collected monthly for 36‐months from six streams. The streams were located a maximum of 118 km apart and drained three different catchment types (forest, urban and rural land uses). We identified repeatable seasonal patterns among bacterial taxa, allowing their separation into three ecological groupings, those following linear, bloom/trough and repeated, seasonal trends. Various physicochemical parameters (light, water and air temperature, pH, dissolved oxygen, nutrients) were linked to temporal community changes. Our models indicate that bloom events and seasonal episodes modify biofilm bacterial populations, suggesting that distinct microbial taxa thrive during these events including non‐cyanobacterial community members. These models could aid in determining how temporal environmental changes affect community assembly and guide the selection of appropriate statistical models to capture future community responses to environmental change.

The possibility that there is a resident and stable commensal microbiome within the pregnant uterus has been supported and refuted by a series of recent studies. One element of most of the initial studies was that they were based primarily on 16S rRNA gene sequencing from bacteria. To account for this limitation, the current study performed both bacterial culture and 16S rRNA gene sequencing in a side-by-side manner (e.g., same tissues isolated from the same animal). The uteruses of 10 mid-pregnant (156 ± 5 d of gestation) Holstein heifers and cows were collected following slaughter. The external surface of the reproductive tract (positive control for contamination during tissue collection) as well as tissues within the pregnant uterus (placentome, inter-cotyledonary placenta, inter-caruncular endometrium, amnionic fluid, allantoic fluid, fetal abomasum content, and fetal meconium) were sampled for bacterial culture and 16S rRNA gene sequencing. There were 87 unique bacterial species cultured from the external surface of the pregnant reproductive tract (contamination control) and 12 bacterial species cultured from pregnancy tissues. Six out of 10 cattle (60%) exhibited bacterial growth in at least one location within the pregnant uterus. For the metataxonomic results (16S rRNA gene sequencing), a low targeted microbial biomass was identified. Analyses of the detected amplicon sequence variants (ASV) revealed that there were: (1) genera that were prevalent on both the external surface and within the pregnant uterus; (2) genera that were prevalent on the external surface but either not detected or had very low prevalence within the pregnant uterus; and (3) genera that were either not detected or had low prevalence on the external surface but found with relatively high prevalence within the pregnant uterus. There are a small number of viable bacteria in the pregnant uterus. The 16S rRNA gene sequencing detected a microbial community within the pregnant uterus but with a low biomass. These results are consistent with recent studies of the pregnant bovine uterus and leave open the question of whether there is adequate microbial mass to significantly affect the biology of the normal healthy bovine pregnancy.

Low microbial biomass within the reproductive tract of mid-lactation dairy cows: A study approach

Microflora for improving the Auricularia auricula spent mushroom substrate for Protaetia brevitarsis production