Sequencing Protocol Research Articles

Optimized bacterial community characterization through full-length 16S rRNA gene sequencing utilizing MinION nanopore technology

BackgroundAccurate identification of bacterial communities is crucial for research applications, diagnostics, and clinical interventions. Although 16S ribosomal RNA (rRNA) gene sequencing is a widely employed technique for bacterial taxonomic classification, it often results in misclassified or unclassified bacterial taxa. This study sought to refine the full-length 16S rRNA gene sequencing protocol using the MinION sequencer, focusing on the V1–V9 regions. Our methodological enquiry examined several factors, including the number of PCR amplification cycles, choice of primers and Taq polymerase, and specific sequence databases and workflows employed. We used a microbial standard comprising eight bacterial strains (five gram-positive and three gram-negative) in known proportions as a validation control.ResultsBased on the MinION protocol, we employed the microbial standard as the DNA template for the 16S rRNA gene amplicon sequencing procedure. Our analysis showed that an elevated number of PCR amplification cycles introduced PCR bias, and the selection of Taq polymerase and primer sets significantly affected the subsequent analysis. Bacterial identification at genus level demonstrated Pearson correlation coefficients ranging from 0.73 to 0.79 when assessed using BugSeq, Kraken-Silva and EPI2ME-16S workflows. Notably, the EPI2ME-16S workflow exhibited the highest Pearson correlation with the microbial standard, minimised misclassification, and increased alignment accuracy. At the species taxonomic level, the BugSeq workflow was superior, with a Pearson correlation coefficient of 0.92.ConclusionsThese findings emphasise the importance of careful selection of PCR settings and a well-structured analytical framework for 16S rRNA full-length gene sequencing. The results showed a robust correlation between the predicted and observed bacterial abundances at both the genus and species taxonomic levels, making these findings applicable across diverse research contexts and with clinical utility for reliable pathogen identification.

Identification of SARS-CoV-2 variants in indoor dust.

Environmental surveillance of pathogens underlying infectious disease is critical to ensure public health. Recent efforts to track SARS-CoV-2 have utilized wastewater sampling to infer community trends in viral abundance and variant composition. Indoor dust has also been used for building-level inferences, though to date no sequencing data providing variant-scale resolution have been reported from dust samples, and strategies to monitor circulating variants in dust are needed to help inform public health decisions. In this study, we demonstrate that SARS-CoV-2 lineages can be detected and sequenced from indoor bulk dust samples. We collected 93 vacuum bags from April 2021 to March 2022 from buildings on The Ohio State University's (OSU) Columbus campus, and the dust was used to develop and apply an amplicon-based whole-genome sequencing protocol to identify the variants present and estimate their relative abundances. Three variants of concern were detected in the dust: Alpha, Delta, and Omicron. Alpha was found in our earliest sample in April 2021 with an estimated frequency of 100%. Delta was the primary variant present from October of 2021 to January 2022, with an average estimated frequency of 91% (±1.3%). Omicron became the primary variant in January 2022 and was the dominant strain in circulation through March with an estimated frequency of 87% (±3.2%). The detection of these variants on OSU's campus correlates with the circulation of these variants in the surrounding population (Delta p<0.0001 and Omicron p = 0.02). Overall, these results support the hypothesis that dust can be used to track COVID-19 variants in buildings.

Comparison of the efficiency of initial dental alignment with Invisalign® aligners changed every 7 or 14 days in mature adults: Randomized clinical trial.

To compare the anterior crowding correction after sequential use of the first 5 aligners between two aligner exchange protocols (7 and 14 days) in mature adult patients. Thirty-six patients over 35 years who received orthodontic treatment with Invisalign® were randomly allocated to two different aligner replacement sequence protocols: Group 1: exchange every 7 days (n = 18); and Group 2: exchange every 14 days (n = 18). All patients were scanned with iTero Element 5D® (Align Technology) in two treatment times: at pre-treatment (T1) and after using the first five aligners (T2). Little's Irregularity Index (LII) and arch widths were evaluated with OrthoCAD software. Intra and intergroup comparisons were performed with the dependent and independent t-tests. The results were considered significant for P < .05. Thirty-five patients completed the study. Both groups' maxillary and mandibular Irregularity Indexesi were significantly lower at T2. There was no significant difference in inter-canine, inter-premolar, and intermolar distances.G2 (14 days) presented a greater decrease in mandibular irregularity than G1 (7 days). Both exchange protocols (7 and 14 days) effectively correct anterior crowding in the initial phase of orthodontic treatment with aligners in mature adult patients. However, the 14-day exchange protocol provided a greater correction in mandibular anterior crowding in the evaluated period than the 7-day exchange protocol.

AGImpute: imputation of scRNA-seq data based on a hybrid GAN with dropouts identification.

Dropout events bring challenges in analyzing single-cell RNA sequencing data as they introduce noise and distort the true distributions of gene expression profiles. Recent studies focus on estimating dropout probability and imputing dropout events by leveraging information from similar cells or genes. However, the number of dropout events differs in different cells, due to the complex factors, such as different sequencing protocols, cell types, and batch effects. The dropout event differences are not fully considered in assessing the similarities between cells and genes, which compromises the reliability of downstream analysis. This work proposes a hybrid Generative Adversarial Network with dropouts identification to impute single-cell RNA sequencing data, named AGImpute. First, the numbers of dropout events in different cells in scRNA-seq data are differentially estimated by using a dynamic threshold estimation strategy. Next, the identified dropout events are imputed by a hybrid deep learning model, combining Autoencoder with a Generative Adversarial Network. To validate the efficiency of the AGImpute, it is compared with seven state-of-the-art dropout imputation methods on two simulated datasets and seven real single-cell RNA sequencing datasets. The results show that AGImpute imputes the least number of dropout events than other methods. Moreover, AGImpute enhances the performance of downstream analysis, including clustering performance, identifying cell-specific marker genes, and inferring trajectory in the time-course dataset. The source code can be obtained from https://github.com/xszhu-lab/AGImpute.

Mirror-Image Phage Display for the Selection of D-Amino Acid Peptide Ligands as Potential Therapeutics.

In neurodegenerative diseases like Alzheimer's disease (AD), endogenous proteins or peptides aggregate with themselves. These proteins may lose their function or aggregates and/or oligomers can obtain toxicity, causing injury or death to cells. Aggregation of two major proteins characterizes AD. Amyloid-β peptide (Aβ) is deposited in amyloid plaques within the extracellular space of the brain and Tau in so-called neurofibrillary tangles in neurons. Finding peptide ligands to halt protein aggregation is a promising therapeutical approach. Using mirror-image phage display with a commercially available, randomized 12-mer peptide library, we have selected D-amino acid peptides, which bind to the Tau protein and modulate its aggregation in vitro. Peptides can bind specifically and selectively to a target molecule, but natural L-amino acid peptides may have crucial disadvantages for in vivo applications, as they are sensitive to protease degradation and may elicit immune responses. One strategy to circumvent these disadvantages is the use of non-naturally occurring D-amino acid peptides as they exhibit increased protease resistance and generally do not activate the immune system. To perform mirror-image phage display, the target protein needs to be synthesized as D-amino acid version. If the target protein sequence is too long to be synthesized properly, smaller peptides derived from the full length protein can be used for the selection process. This also offers the possibility to influence the binding region of the selected D-peptides in the full-length target protein. Here we provide the protocols for mirror-image phage display selection on the PHF6* peptide of Tau, based on the commercially available Ph.D.™-12 Phage Display Peptide Library Kit, leading to D-peptides that also bind the full length Tau protein (Tau441), next to PHF6*. In addition, we provide protocols and data for the first characterization of those D-peptides that inhibit Tau aggregation in vitro. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Mirror image phage display selection against D-PHF6* fibrils Support Protocol 1: Single phage ELISA Basic Protocol 2: Sequencing and D-peptide generation Basic Protocol 3: Thioflavin-T (ThT) test to control inhibition of Tau aggregation Support Protocol 2: Purification of full-length Tau protein Basic Protocol 4: ELISA to demonstrate the binding of the generated D-peptides to PHF6* and full-length Tau fibrils.

Abstract B033: Mapping subclonal epigenetic evolution in colorectal cancer by spatial analysis of DNA hypermethylation

Abstract Aberrant patterns of DNA methylation (DNAme) have long been noted in colorectal cancer (CRC). Early studies found overall hypomethylation of the cancer genome, while subsequent work revealed focal hypermethylation at specific loci, especially CpG-rich promoters. Loci occupied by polycomb repressive complex 2 in stem cells are remarkably enriched in cancer-specific hypermethylation events. These Polycomb Target Genes (PTGs) include important transcriptional regulators of lineage specification and differentiation, suggesting that hypermethylation-mediated silencing of PTGs could play an active role in CRC initiation or progression. Despite these findings, we have limited knowledge of when, where, and how this hypermethylation arises. Preliminary evidence from bulk tumor samples in the Cancer Genome Atlas suggests that many of these PTG hypermethylation events may be almost completely clonal. Additionally, we have noted rare, densely methylated reads covering PTGs in cancer-adjacent, histologically normal tissue. These observations suggest that PTG hypermethylation may be a very early event in carcinogenesis and may play a permissive or even active role in that process. To better understand the timing and evolution of PTG hypermethylation events in CRC, we have developed a protocol that allows us to extract dozens of small (20µL), spatially annotated mini-bulk samples from live tumors. These mini-bulks may be frozen or dissociated to viable single-cell suspensions. Remaining tumor tissue is preserved in the form of spatially annotated FFPE blocks, which can be used for analyses such as high-plex immunofluorescence or spatial transcriptomics. Using this process, we have collected over 500 spatially annotated samples from 6 CRC cases, including 196 micro-bulk samples profiled using the Infinium MethylationEPIC array. Additionally, we have profiled DNAme in 147 single cells using a dramatically improved single-cell whole-genome bisulfite sequencing protocol developed in our lab. Analysis of EPIC array data reveals wide variation in DNAme heterogeneity between tumors. While in some tumors, the vast majority of DNA hypermethylation events are clonal, other tumors reveal significant intra-tumor heterogeneity, including two or more prominent DNAme subclones as well as a substantial number of ‘private’ hypermethylation events that occur in only one sample. Mapping DNAme information back onto our spatial data reveals that in at least one case, DNAme clones are spatially partitioned and are associated with distinct histology. Ongoing work includes inference of phylogenetic trees from DNA hypermethylation events using non-reversible models of methylation accumulation, allowing us to measure the relative timing of hypermethylation events, as well as integration of array, whole-genome, and single-cell methylation data to more completely characterize DNAme subclones, characterize cellular DNAme heterogeneity at variably methylated sites, and shed further light on the evolution of cancer-related DNA hypermethylation. Citation Format: Nathan J. Spix, Hsiao-yun Milliron, Manpreet Kalkat, Emily Eugster, David W. Chesla, David Sokol, Emily Jung, Paula Nolte, Kelly K. Krzyzanowski, Toshinori Hinoue, Hui Shen, Peter W. Laird. Mapping subclonal epigenetic evolution in colorectal cancer by spatial analysis of DNA hypermethylation [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B033.

Dysbiosis of Gut Microbiota in Patients with Chronic Kidney Disease.

Objective The gut bacterial microbiota is altered in patients with chronic kidney disease (CKD). However, the bacterial composition at each stage of CKD is unclear in these patients, including those receiving renal replacement therapy. We herein report the changes in the gut microbiota among patients with CKD. Methods A total of 93 individuals were recruited for the study. Seventy-three patients had stage 3-5 CKD, including those receiving renal replacement therapy (CKD group), and 20 were age- and sex-matched controls (CKD stage 1-2). The gut microbiome composition was analyzed using a 16S ribosomal RNA gene-based sequencing protocol. Results At the genus level, the butyrate-producing bacteria Lachnospira, Blautia, Coprococcus, Anaerostipes, and Roseburia were more abundant in the control group (linear discriminant analysis score of >3) than in the CKD group. Lachnospira was more abundant in the control group than in patients with CKD stage 3a. Compared to the control group, multiplex butyrate-producing bacteria were deficient in patients with CKD stage 3b-5D, including in patients receiving renal replacement therapy. Conclusion Our findings highlight the fact that the gut bacterial composition, including butyrate-producing bacteria, deteriorates from CKD stage 3b. Even after renal replacement therapy, the bacterial composition did not change.

Time-Saving 3D MR Imaging Protocols with Millimeter and Submillimeter Isotropic Spatial Resolution for Face and Neck Imaging as Implemented at a Single-Site Major Referral Center.

MR imaging has become the routine technique for staging nasopharyngeal carcinoma, evaluating perineural tumor spread, and detecting cartilage invasion in laryngeal carcinoma. However, these protocols traditionally require in the range of 25 to 35 minutes of acquisition time. 3D sequences offer the potential advantage of time savings through the acquisition of 1-mm or submillimeter resolution isotropic data followed by multiplanar reformats that require no further imaging time. We have iteratively optimized vendor product 3D T1-weighted MR imaging sequences for morphologic face and neck imaging, reducing the average acquisition time of our 3T protocols by 9 minutes 57 seconds (40.9%) and of our 1.5T protocols by 9 minutes 5 seconds (37.0%), while simultaneously maintaining or improving spatial resolution. This clinical report describes our experience optimizing and implementing commercially available 3D T1-weighted MR imaging pulse sequence protocols for clinical face and neck MR imaging examinations using illustrative cases. We provide protocol details to allow others to replicate our implementations, and we report challenges we faced along with our solutions.

Seq2Sat and SatAnalyzer toolkit: Towards comprehensive microsatellite genotyping from sequencing data.

Accurate and efficient microsatellite loci genotyping is an essential process in population genetics that is also used in various demographic analyses. Protocols for next-generation sequencing of microsatellite loci enable high-throughput and cross-compatible allele scoring, common issues that are not addressed by conventional capillary-based approaches. To improve this process, we have developed an all-in-one software, called Seq2Sat (sequence to microsatellite), in C++ to support automated microsatellite genotyping. It directly takes raw reads of microsatellite amplicons and conducts read quality control before inferring genotypes based on depth-of-read, read ratio, sequence composition and length. We have also developed a module for sex identification based on sex chromosome-specific locus amplicons. To allow for greater user access and complement autoscoring, we developed SatAnalyzer (microsatellite analyzer), a user-friendly web-based platform that conducts reads-to-report analyses by calling Seq2Sat for genotype autoscoring and produces interactive genotype graphs for manual editing. SatAnalyzer also allows users to troubleshoot multiplex optimization by analysing read quality and distribution across loci and samples in support of high-quality library preparation. To evaluate its performance, we benchmarked our toolkit Seq2Sat/SatAnalyzer against a conventional capillary gel method and existing microsatellite genotyping software, MEGASAT, using two datasets. Results showed that SatAnalyzer can achieve >99.70% genotyping accuracy and Seq2Sat is ~5 times faster than MEGASAT despite many more informative tables and figures being generated. Seq2Sat and SatAnalyzer are freely available on github (https://github.com/ecogenomicscanada/Seq2Sat) and dockerhub (https://hub.docker.com/r/rocpengliu/satanalyzer).

Tracking arboviruses, their transmission vectors and potential hosts by nanopore sequencing of mosquitoes.

The risk to human health from mosquito-borne viruses such as dengue, chikungunya and yellow fever is increasing due to increased human expansion, deforestation and climate change. To anticipate and predict the spread and transmission of mosquito-borne viruses, a better understanding of the transmission cycle in mosquito populations is needed. We present a pathogen-agnostic combined sequencing protocol for identifying vectors, viral pathogens and their hosts or reservoirs using portable Oxford Nanopore sequencing. Using mosquitoes collected in São Paulo, Brazil, we extracted RNA for virus identification and DNA for blood meal and mosquito identification. Mosquitoes and blood meals were identified by comparing cytochrome c oxidase I (COI) sequences against a curated Barcode of Life Data System (BOLD). Viruses were identified using the SMART-9N protocol, which allows amplified DNA to be prepared with native barcoding for nanopore sequencing. Kraken 2 was employed to detect viral pathogens and Minimap2 and BOLD identified the contents of the blood meal. Due to the high similarity of some species, mosquito identification was conducted using blast after generation of consensus COI sequences using RACON polishing. This protocol can simultaneously uncover viral diversity, mosquito species and mosquito feeding habits. It also has the potential to increase understanding of mosquito genetic diversity and transmission dynamics of zoonotic mosquito-borne viruses.

Wide-spread dispersal in a deep-sea brooding polychaete: the role of natural history collections in assessing the distribution in quill worms (Onuphidae, Annelida)

BackgroundModern integrative taxonomy-based annelid species descriptions are detailed combining morphological data and, since the last decades, also molecular information. Historic species descriptions are often comparatively brief lacking such detail. Adoptions of species names from western literature in the past led to the assumption of cosmopolitan ranges for many species, which, in many cases, were later found to include cryptic or pseudocryptic lineages with subtle morphological differences. Natural history collections and databases can aid in assessing the geographic ranges of species but depend on correct species identification. Obtaining DNA sequence information from wet-collection museum specimens of marine annelids is often impeded by the use of formaldehyde and/or long-term storage in ethanol resulting in DNA degradation and cross-linking.ResultsThe application of ancient DNA extraction methodology in combination with single-stranded DNA library preparation and target gene capture resulted in successful sequencing of a 110-year-old collection specimen of quill worms. Furthermore, a 40-year-old specimen of quill worms was successfully sequenced using a standard extraction protocol for modern samples, PCR and Sanger sequencing. Our study presents the first molecular analysis of Hyalinoecia species including the previously known species Hyalinoecia robusta, H. tubicloa, H. artifex, and H. longibranchiata, and a potentially undescribed species from equatorial western Africa morphologically indistinguishable from H. tubicola. The study also investigates the distribution of these five Hyalinoecia species. Reassessing the distribution of H. robusta reveals a geographical range covering both the Atlantic and the Indian Oceans as indicated by molecular data obtained from recent and historical specimens.ConclusionOur results represent an example of a very wide geographical distribution of a brooding deep-sea annelid with a complex reproduction strategy and seemingly very limited dispersal capacity of its offspring, and highlights the importance of molecular information from museum specimens for integrative annelid taxonomy and biogeography.

Internal and external normalization of nascent RNA sequencing run-on experiments

In experiments with significant perturbations to transcription, nascent RNA sequencing protocols are dependent on external spike-ins for reliable normalization. Unlike in RNA-seq, these spike-ins are not standardized and, in many cases, depend on a run-on reaction that is assumed to have constant efficiency across samples. To assess the validity of this assumption, we analyze a large number of published nascent RNA spike-ins to quantify their variability across existing normalization methods. Furthermore, we develop a new biologically-informed Bayesian model to estimate the error in spike-in based normalization estimates, which we term Virtual Spike-In (VSI). We apply this method both to published external spike-ins as well as using reads at the 3′\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$3^\\prime$$\\end{document} end of long genes, building on prior work from Mahat (Mol Cell 62(1):63–78, 2016. https://doi.org/10.1016/j.molcel.2016.02.025) and Vihervaara (Nat Commun 8(1):255, 2017. https://doi.org/10.1038/s41467-017-00151-0). We find that spike-ins in existing nascent RNA experiments are typically under sequenced, with high variability between samples. Furthermore, we show that these high variability estimates can have significant downstream effects on analysis, complicating biological interpretations of results.

An amplicon-based protocol for whole-genome sequencing of human respiratory syncytial virus subgroup A.

It is convenient to study complete genome sequences of human respiratory syncytial virus (hRSV) for ongoing genomic characterization and identification of highly transmissible or pathogenic variants. Whole genome sequencing of hRSV has been challenging from respiratory tract specimens with low viral loads. Herein, we describe an amplicon-based protocol for whole genome sequencing of hRSV subgroup A validated with 24 isolates from nasopharyngeal swabs and infected cell cultures, which showed cycle threshold (Ct) values ranging from 10 to 31, as determined by quantitative reverse-transcription polymerase chain reaction. MinION nanopore generated 3200 to 5400 reads per sample to sequence over 93% of the hRSV-A genome. Coverage of each contig ranged from 130× to 200×. Samples with Ct values of 20.9, 25.2, 27.1, 27.7, 28.2, 28.8, and 29.6 led to the sequencing of over 99.0% of the virus genome, indicating high genome coverage even at high Ct values. This protocol enables the identification of hRSV subgroup A genotypes, as primers were designed to target highly conserved regions. Consequently, it holds potential for application in molecular epidemiology and surveillance of this hRSV subgroup.

Genome stability assessment of PRRS vaccine strain with new ARTIC-style sequencing protocol.

A tiling amplicon sequencing protocol was developed to analyse the genome sequence stability of the modified live PRRSV vaccine strain, Porcilis MLV. The backbone of the ARTIC-style protocol was formed by 34 individual primer pairs, which were divided into two primer pools. Primer pairs were designed to amplify 532 to 588 bp fragments of the corresponding genomic region. The amplicons are suitable for sequencing on Illumina DNA sequencers with available 600-cycle sequencing kits. The concentration of primer pairs in the pools was optimized to obtain a balanced sequencing depth along the genome. Deep sequencing data of three vaccine batches were also analysed. All three vaccine batches were very similar to each other, although they also showed single nucleotide variations (SNVs) affecting less than 1 % of the genome. In the three vaccine strains, 113 to 122 SNV sites were identified; at these sites, the minority variants represented a frequency range of 1 to 48.7 percent. Additionally, the strains within the batches contained well-known length polymorphisms; the genomes of these minority deletion mutants were 135 to 222 bp shorter than the variant with the complete genome. Our results show the usefulness of ARTIC-style protocols in the evaluation of the genomic stability of PRRS MLV strains.

Amplicon sequencing with internal standards yields accurate picocyanobacteria cell abundances as validated with flow cytometry.

To understand ecosystem state and function, marine microbial ecologists seek measurements of organismal abundance and diversity at high taxonomic resolution. Conventional flow cytometry accurately estimates microbial cell abundance but only discerns broad groups with distinct optical properties. While amplicon sequencing resolves more comprehensive diversity within microbiomes, it typically only provides relative organismal abundances within samples, not absolute abundance changes. Internal genomic standards offer a solution for absolute amplicon-based measures. Here, we spiked genomic standards into plankton samples from surface seawater, gathered at 46-km intervals along a cruise transect spanning the southern California Current System and the oligotrophic North Pacific Subtropical Gyre. This enabled evaluation of the absolute volumetric gene copy abundances of 16S rRNA amplicon sequence variants (amplified with 515Y-926R universal primers, quantitatively validated with mock communities) and cell abundances of picocyanobacteria with known genomic 16S copy numbers. Comparison of amplicon-derived cell abundances of Prochlorococcus and Synechococcus with flow cytometry data from nearby locations yielded nearly identical results (slope = 1.01; Pearson's r = 0.9942). Our findings show that this amplicon sequencing protocol combined with genomic internal standards accurately measures absolute cell counts of marine picocyanobacteria in complex field samples. By extension, we expect this approach to reasonably estimate volumetric gene copies for other amplified taxa in these samples.

Development and application of a whole genome amplicon sequencing method for infectious salmon anemia virus (ISAV).

Infectious salmon anemia (ISA) is an infectious disease primarily affecting farmed Atlantic salmon, Salmo salar, which is caused by the ISA virus (ISAV). ISAV belongs to the Orthomyxoviridae family. The disease is a serious condition resulting in reduced fish welfare and high mortality. In this study, we designed an amplicon-based sequencing protocol for whole genome sequencing of ISAV. The method consists of 80 ISAV-specific primers that cover 92% of the virus genome and was designed to be used on an Illumina MiSeq platform. The sequencing accuracy was investigated by comparing sequences with previously published Sanger sequences. The sequences obtained were nearly identical to those obtained by Sanger sequencing, thus demonstrating that sequences produced by this amplicon sequencing protocol had an acceptable accuracy. The amplicon-based sequencing method was used to obtain the whole genome sequence of 12 different ISAV isolates from a small local epidemic in the northern part of Norway. Analysis of the whole genome sequences revealed that segment reassortment took place between some of the isolates and could identify which segments that had been reassorted.

Generating Neuroimmune Assembloids Using Human Induced Pluripotent Stem Cell (iPSC)-Derived Cortical Organoids and Microglia.

The emergence of brain organoids has revolutionized our understanding of neurodevelopment and neurological diseases by providing an in vitro model system that recapitulates key aspects of human brain development. However, conventional organoid protocols often overlook the role of microglia, the resident immune cells of the central nervous system. Microglia dysfunction is implicated in various neurological disorders, highlighting the need for their inclusion in organoid models. Here, we present a novel method for generating neuroimmune assembloids using human-induced pluripotent stem cell (iPSC)-derived cortical organoids and microglia. Building upon our previous work generating myelinating cortical organoids, we extend our methodology to include the integration of microglia, ensuring their long-term survival and maturation within the organoids. We describe two integration methods: one involving direct addition of microglia progenitors to the organoids and an alternative approach where microglia and dissociated neuronal progenitors are aggregated together in a defined ratio. To facilitate downstream analysis, we also describe a dissociation protocol for single-cell RNA sequencing (scRNA-seq) and provide guidance on fixation, cryosectioning, and immunostaining of assembloid structures. Overall, our protocol provides a comprehensive framework for generating neuroimmune assembloids, offering researchers a valuable tool for studying the interactions between neural cell types and immune cells in the context of neurological diseases.

Emergence of pathogenic bacteria isolates from zea maize extract using 16s rRNA molecular sequencing protocol as a tools for microbial identification and characterization

The purpose of this research work is to determine the molecular identity of bacteria isolated from infected Zea maize using the 16s rRNA molecular sequencing protocol. The samples were obtained from Okeagbe, Akoko north-west local government in Ondo state with latitude and longitude of Okeagbe at 7.6450° N, and 5.7603° E respectively. Preparation of infected maize samples was cultured using the serial dilution method.. Confirmatory characterization of bacteria isolates using 16s rRNA (ribosomal RNA) sequencing procedures (purification, amplication, Sequencing, and DNA extraction) inclusive.The result shows the isolation of the bacteria isolates involved the culturing, inoculation, and plating of the isolate on a plated agar, the identification of the bacteria isolate includes the use of Gram staining, biochemical tests, and characterization using Bergey's manual and antibiotics Susceptibility Test. In Gram staining all bacteria isolates were positive except one, in the biochemical test most bacteria isolate was positive for sugar Fermentation and citrate test and all were negative for the Voges Proskauer test. In antibiotics Susceptibility test few were sensitive, most were susceptible to antibiotics used. With the use of the 16S rRNA and procedures (purification and application of product, Sequencing, and Extraction of DNA) the bacteria isolate were identified and characterized. The phylogenetic analysis and molecular identification of 16S rDNA sequencing revealed that Escherichia coli, Samonella enterica and Staphylococcus aureus were found to infect maize. Molecular characterization based on 16S rRNA Gene sequencing confirms the identity of bacteria. The conventional procedure shows the presence of different arrays of microorganisms in the infected maize, microbes identified are Bacillus subtilis, Bacillus anthracis, Micrococcus luteus, Clostridium sporogenes, Microbacterium lacticum, Clostridium sporogenes, Lactobacillus casei and Micrococcus luteus. The phylogenetic analysis and molecular identification of 16s rRNA sequencing revealed that Escherichia coli, Samonella enterica and Staphylococcus aureus were found to infect maize in Band fragment Base pair 1500bp. In conclusion, the hearsay that maize can only be infected by fungi, it was observed that the possibility of being infected with pathogenic bacteria is imminent. The bottom line is, there should be proper surveillance and food safety in our farm, market and food store, to prevent and totally eradicate emergence of pathogenic organism in our food item.

Whole-Genome Bisulfite Sequencing Protocol for the Analysis of Genome-Wide DNA Methylation and Hydroxymethylation Patterns at Single-Nucleotide Resolution.

The analysis of genome-wide epigenomic alterations including DNA methylation and hydroxymethylation has become a subject of intensive research for many biological and clinical questions. DNA methylation analysis bears the particular promise to supplement or replace biochemical and imaging-based tests for the next generation of personalized medicine. Whole-genome bisulfite sequencing (WGBS) using next-generation sequencing technologies is currently considered the gold standard for a comprehensive and quantitative analysis of DNA methylation throughout the genome. However, bisulfite conversion does not allow distinguishing between cytosine methylation and hydroxymethylation requiring an additional chemical or enzymatic step to identify hydroxymethylated cytosines. Here, we provide a detailed protocol based on a commercial kit for the preparation of sequencing libraries for the comprehensive whole-genome analysis of DNA methylation and/or hydroxymethylation. The protocol is based on the construction of sequencing libraries from limited amounts of input DNA by ligation of methylated adaptors to the fragmented DNA prior to bisulfite conversion. For analyses requiring a quantitative distinction between 5-methylcytosine and 5-hydroxymethylcytosines levels, an oxidation step is included in the same workflow to perform oxidative bisulfite sequencing (OxBs-Seq). In this case, two sequencing libraries will be generated and sequenced: a classic methylome following bisulfite conversion and analyzing modified cytosines (not distinguishing between methylated and hydroxymethylated cytosines) and a methylome analyzing only methylated cytosines, respectively. Hydroxymethylation levels are deduced from the differences between the two reactions. We also provide a step-by-step description of the data analysis using publicly available bioinformatic tools. The described protocol has been successfully applied to different human and plant samples and yields robust and reproducible results.

An approach for developing a blood-based screening panel for lung cancer based on clonal hematopoietic mutations.

Early detection can significantly reduce mortality due to lung cancer. Presented here is an approach for developing a blood-based screening panel based on clonal hematopoietic mutations. Animal model studies suggest that clonal hematopoietic mutations in tumor infiltrating immune cells can modulate cancer progression, representing potential predictive biomarkers. The goal of this study was to determine if the clonal expansion of these mutations in blood samples could predict the occurrence of lung cancer. A set of 98 potentially pathogenic clonal hematopoietic mutations in tumor infiltrating immune cells were identified using sequencing data from lung cancer samples. These mutations were used as predictors to develop a logistic regression machine learning model. The model was tested on sequencing data from a separate set of 578 lung cancer and 545 non-cancer samples from 18 different cohorts. The logistic regression model correctly classified lung cancer and non-cancer blood samples with 94.12% sensitivity (95% Confidence Interval: 92.20-96.04%) and 85.96% specificity (95% Confidence Interval: 82.98-88.95%). Our results suggest that it may be possible to develop an accurate blood-based lung cancer screening panel using this approach. Unlike most other "liquid biopsies" currently under development, the approach presented here is based on standard sequencing protocols and uses a relatively small number of rationally selected mutations as predictors.