Bioinformatics Research Articles

High-throughput nanopore DNA sequencing of large insert fosmid clones directly from bacterial colonies.

Fosmids and cosmids are vectors frequently used in functional metagenomic studies. With a large insert capacity (around 30 kb) they can encode dozens of cloned genes or in some cases, entire biochemical pathways. Fosmids with cloned inserts can be transferred to heterologous hosts and propagated to enable screening for new enzymes and metabolites. After screening, fosmids from clones with an activity of interest must be de novo sequenced, a critical step toward the identification of the gene(s) of interest. In this work, we present a new approach for rapid and high-throughput fosmid sequencing directly from Escherichia coli colonies without liquid culturing or fosmid purification. Our sample preparation involves fosmid amplification with phi29 polymerase and then direct nanopore sequencing using the Oxford Nanopore Technologies system. We also present a bioinformatics pipeline termed "phiXXer" that facilitates both de novo read assembly and vector trimming to generate a linear sequence of the fosmid insert. Finally, we demonstrate the accurate sequencing of 96 fosmids in a single run and validate the method using two fosmid libraries that contain cloned large insert (~30-40 kb) genomic or metagenomic DNA.IMPORTANCELarge-insert clone (fosmids or cosmids) sequencing is challenging and arguably the most limiting step of functional metagenomic screening workflows. Our study establishes a new method for high-throughput nanopore sequencing of fosmid clones directly from lysed Escherichia coli cells. It also describes a companion bioinformatic pipeline that enables de novo assembly of fosmid DNA insert sequences. The devised method widens the potential of functional metagenomic screening by providing a simple, high-throughput approach to fosmid clone sequencing that dramatically speeds the pace of discovery.

Genotyping-by-sequencing-based high-resolution mapping reveals a single candidate gene for the grapevine veraison locus Ver1.

Veraison marks the transition from berry growth to berry ripening and is a crucial phenological stage in grapevine (Vitis vinifera): the berries become soft and begin to accumulate sugars, aromatic substances, and, in red cultivars, anthocyanins for pigmentation, while the organic acid levels begin to decrease. These changes determine the potential quality of wine. However, rising global temperatures lead to earlier flowering and ripening, which strongly influence wine quality. Here, we combined genotyping-by-sequencing with a bioinformatics pipeline on ∼150 F1 genotypes derived from a cross between the early ripening variety 'Calardis Musqué' and the late-ripening variety 'Villard Blanc'. Starting from 20,410 haplotype-based markers, we generated a high-density genetic map and performed a quantitative trait locus analysis based on phenotypic datasets evaluated over 20 years. Through locus-specific-marker-enrichment and recombinant screening of ∼1000 additional genotypes, we refined the originally postulated 5 Mb veraison locus, Ver1, on chromosome 16 to only 112 kb, allowing us to pinpoint the ethylene response factor (ERF) VviERF027 (VCost.v3 gene ID: Vitvi16g00942, CRIBIv1 gene ID: VIT_16s0100g00400) as veraison candidate gene. Furthermore, the early veraison allele could be traced back to a clonal 'Pinot' variant first mentioned in the 17th century. 'Pinot Precoce Noir' passed this allele over 'Madeleine Royale' to the maternal grandparent 'Bacchus Weiss' and, ultimately, to the maternal parent 'Calardis Musqué'. Our findings are crucial for ripening time control, thereby improving wine quality, and for breeding grapevines adjusted to climate change scenarios that have a major impact on agro-ecosystems in altering crop plant phenology.

INCREASING THE REPRODUCIBILITY OF SCIENTIFIC RESEARCH WORKS: A CASE STUDY USING THE ENVIRONMENT CODE-FIRST FRAMEWORK

Objective: The purpose of this paper is to present a case study on how a recently proposed reproducibility framework named Environment Code-First (ECF) based on the Infrastructure-as-Code approach can improve the implementation and reproduction of computing environments by reducing complexity and manual intervention. Methodology: The study compares the manual way of implementing a pipeline and the automated method proposed by the ECF framework, showing real metrics regarding time consumption, efforts, manual intervention, and platform agnosticism. It details the steps needed to implement the computational environment of a bioinformatics pipeline named MetaWorks from the perspective of the scientist who owns the research work. Also, we present the steps taken to recreate the environment from the point of view of one who wants to reproduce the published results of a research work. Findings and Conclusion: The results demonstrate considerable benefits in adopting the ECF framework, particularly in maintaining the same applicational behavior across different machines. Such empirical evidence underscores the significance of reducing manual intervention, as it ensures the consistent recreation of the environment as many times as needed, especially by non-original researchers. Originality/Value: Verifying published findings in bioinformatics through independent validation is challenging, mainly when accounting for differences in software and hardware to recreate computational environments. Reproducing a computational environment that closely mimics the original proves intricate and demands a significant investment of time. This study contributes to educate and assist researchers in enhancing the reproducibility of their work by creating self-contained computational environments that are highly reproducible, isolated, portable, and platform-agnostic.

Increased Diagnostic Yield by Reanalysis of Whole Exome Sequencing Data in Mitochondrial Disease.

The genetic diagnosis of mitochondrial disorders is complicated by its genetic and phenotypic complexity. Next generation sequencing techniques have much improved the diagnostic yield for these conditions. A cohort of individuals with multiple respiratory chain deficiencies, reported in the literature 10 years ago, had a diagnostic rate of 60% by whole exome sequencing (WES) but 40% remained undiagnosed. We aimed to identify a genetic diagnosis by reanalysis of the WES data for the undiagnosed arm of this 10-year-old cohort of patients with suspected mitochondrial disorders. The WES data was transferred and processed by the RD-Connect Genome-Phenome Analysis Platform (GPAP) using their standardized pipeline. Variant prioritisation was carried out on the RD-Connect GPAP. Singleton WES data from 14 individuals was reanalysed. We identified a possible or likely genetic diagnosis in 8 patients (8/14, 57%). The variants identified were in a combination of mitochondrial DNA (n = 1, MT-TN), nuclear encoded mitochondrial genes (n = 2, PDHA1, and SUCLA2) and nuclear genes associated with nonmitochondrial disorders (n = 5, PNPLA2, CDC40, NBAS and SLC7A7). Variants in both the NBAS and CDC40 genes were established as disease causing after the original cohort was published. We increased the diagnostic yield for the original cohort by 15% without generating any further genomic data. In the era of multiomics we highlight that reanalysis of existing WES data is a valid tool for generating additional diagnosis in patients with suspected mitochondrial disease, particularly when more time has passed to allow for new bioinformatic pipelines to emerge, for the development of new tools in variant interpretation aiding in reclassification of variants and the expansion of scientific knowledge on additional genes.

ConsensusPrime—A Bioinformatic Pipeline for Efficient Consensus Primer Design—Detection of Various Resistance and Virulence Factors in MRSA—A Case Study

Background: The effectiveness and reliability of diagnostic tests that detect DNA sequences largely hinge on the quality of the used primers and probes. This importance is especially evident when considering the specific sample being analyzed, as it affects the molecular background and potential for cross-reactivity, ultimately determining the test’s performance. Methods: Predicting primers based on the consensus sequence of the target has multiple advantages, including high specificity, diagnostic reliability, broad applicability, and long-term validity. Automated curation of the input sequences ensures high-quality primers and probes. Results: Here, we present a use case for developing a set of consensus primers and probes to identify antibiotic resistance and virulence genes in Staphylococcus (S.) aureus using the ConsensusPrime pipeline. Extensive qPCR experiments with several S. aureus strains confirm the exceptional quality of the primers designed using the pipeline. Conclusions: By improving the quality of the input sequences and using the consensus sequence as a basis, the ConsensusPrime pipeline pipeline ensures high-quality primers and probes, which should be the basis of molecular assays.

Exome Sequencing has a high diagnostic rate in sporadic congenital hypopituitarism and reveals novel candidate genes.

The pituitary gland is key for childhood growth, puberty, and metabolism. Pituitary dysfunction is associated with a spectrum of phenotypes, from mild to severe. Congenital Hypopituitarism (CH) is the most commonly reported pediatric endocrine dysfunction with an incidence of 1:4000, yet low rates of genetic diagnosis have been reported. We aimed to unveil the genetic etiology of CH in a large cohort of patients from Argentina. We performed whole exome sequencing of 137 unrelated cases of CH, the largest cohort examined with this method to date. Of the 137 cases, 19.1% and 16% carried pathogenic or likely pathogenic variants in known and new genes, respectively, while 28.2% carried variants of uncertain significance. This high yield was achieved through the integration of broad gene panels (genes described in animal models and/or other disorders), an unbiased candidate gene screen with a new bioinformatics pipeline (including genes high loss of function intolerance), and analysis of copy number variants. Three novel findings emerged. First, the most prevalent affected gene encodes the cell adhesion factor ROBO1. Affected children had a spectrum of phenotypes, consistent with a role beyond pituitary stalk interruption syndrome. Second, we found that CHD7 mutations also produce a phenotypic spectrum, not always associated with full CHARGE syndrome. Third, we add new evidence of pathogenicity in the genes PIBF1 and TBC1D32, and report 13 novel candidate genes associated with CH (e.g. PTPN6, ARID5B). Overall, these results provide an unprecedented insight into the diverse genetic etiology of hypopituitarism.

Disregarding multimappers leads to biases in the functional assessment of NGS data

BackgroundStandard ChIP-seq and RNA-seq processing pipelines typically disregard sequencing reads whose origin is ambiguous (“multimappers”). This usual practice has potentially important consequences for the functional interpretation of the data: genomic elements belonging to clusters composed of highly similar members are left unexplored.ResultsIn particular, disregarding multimappers leads to the underrepresentation in epigenetic studies of recently active transposable elements, such as AluYa5, L1HS and SVAs. Furthermore, this common strategy also has implications for transcriptomic analysis: members of repetitive gene families, such the ones including major histocompatibility complex (MHC) class I and II genes, are under-quantified.ConclusionRevealing inherent biases that permeate routine tasks such as functional enrichment analysis, our results underscore the urgency of broadly adopting multimapper-aware bioinformatic pipelines –currently restricted to specific contexts or communities– to ensure the reliability of genomic and transcriptomic studies.

Presence of phage-plasmids in multiple serovars of Salmonella enterica.

Evidence is accumulating in the literature that the horizontal spread of antimicrobial resistance (AMR) genes mediated by bacteriophages and bacteriophage-like plasmid (phage-plasmid) elements is much more common than previously envisioned. For instance, we recently identified and characterized a circular P1-like phage-plasmid harbouring a bla CTX-M-15 gene conferring extended-spectrum beta-lactamase (ESBL) resistance in Salmonella enterica serovar Typhi. As the prevalence and epidemiological relevance of such mechanisms has never been systematically assessed in Enterobacterales, in this study we carried out a follow-up retrospective analysis of UK Salmonella isolates previously sequenced as part of routine surveillance protocols between 2016 and 2021. Using a high-throughput bioinformatics pipeline we screened 47 784 isolates for the presence of the P1 lytic replication gene repL, identifying 226 positive isolates from 25 serovars and demonstrating that phage-plasmid elements are more frequent than previously thought. The affinity for phage-plasmids appears highly serovar-dependent, with several serovars being more likely hosts than others; most of the positive isolates (170/226) belonged to S. Typhimurium ST34 and ST19. The phage-plasmids ranged between 85.8 and 98.2 kb in size, with an average length of 92.1 kb; detailed analysis indicated a high amount of diversity in gene content and genomic architecture. In total, 132 phage-plasmids had the p0111 plasmid replication type, and 94 the IncY type; phylogenetic analysis indicated that both horizontal and vertical gene transmission mechanisms are likely to be involved in phage-plasmid propagation. Finally, phage-plasmids were present in isolates that were resistant and non-resistant to antimicrobials. In addition to providing a first comprehensive view of the presence of phage-plasmids in Salmonella, our work highlights the need for a better surveillance and understanding of phage-plasmids as AMR carriers, especially through their characterization with long-read sequencing.

Exploring the putative microRNAs cross-kingdom transfer in Solanum lycopersicum-Meloidogyne incognita interactions

IntroductionPlant-pathogen interaction is an inexhaustible source of information on how to sustainably control diseases that negatively affect agricultural production. Meloidogyne incognita is a root-knot nematode (RKN), representing a pest for many crops, including tomato (Solanum lycopersicum). RKNs are a global threat to agriculture, especially under climate change, and RNA technologies offer a potential alternative to chemical nematicides. While endogenous microRNAs have been identified in both S. lycopersicum and M. incognita, and their roles have been related to the regulation of developmental changes, no study has investigated the miRNAs cross-kingdom transfer during this interaction.MethodsHere, we propose a bioinformatics pipeline to highlight potential miRNA-dependent cross-kingdom interactions between tomato and M. incognita.ResultsThe obtained data show that nematode miRNAs putatively targeting tomato genes are mostly related to detrimental effects on plant development and defense. Similarly, tomato miRNAs putatively targeting M. incognita biological processes have negative effects on digestion, mobility, and reproduction. To experimentally test this hypothesis, an in vitro feeding assay was carried out using sly-miRNAs selected from the bioinformatics approach. The results show that two tomato miRNAs (sly-miRNA156a, sly-miR169f) soaked by juvenile larvae (J2s) affected their ability to infect plant roots and form galls. This was also coupled with a significant downregulation of predicted target genes (Minc11367, Minc00111), as revealed by a qRT-PCR analysis.DiscussionsTherefore, the current study expands the knowledge related to the cross-kingdom miRNAs involvement in host-parasite interactions and could pave the way for the application of exogenous plant miRNAs as tools to control nematode infection.

Fecal microbiota transplantation: current challenges and future landscapes.

SUMMARYGiven the importance of gut microbial homeostasis in maintaining health, there has been considerable interest in developing innovative therapeutic strategies for restoring gut microbiota. One such approach, fecal microbiota transplantation (FMT), is the main "whole gut microbiome replacement" strategy and has been integrated into clinical practice guidelines for treating recurrent Clostridioides difficile infection (rCDI). Furthermore, the potential application of FMT in other indications such as inflammatory bowel disease (IBD), metabolic syndrome, and solid tumor malignancies is an area of intense interest and active research. However, the complex and variable nature of FMT makes it challenging to address its precise functionality and to assess clinical efficacy and safety in different disease contexts. In this review, we outline clinical applications, efficacy, durability, and safety of FMT and provide a comprehensive assessment of its procedural and administration aspects. The clinical applications of FMT in children and cancer immunotherapy are also described. We focus on data from human studies in IBD in contrast with rCDI to delineate the putative mechanisms of this treatment in IBD as a model, including colonization resistance and functional restoration through bacterial engraftment, modulating effects of virome/phageome, gut metabolome and host interactions, and immunoregulatory actions of FMT. Furthermore, we comprehensively review omics technologies, metagenomic approaches, and bioinformatics pipelines to characterize complex microbial communities and discuss their limitations. FMT regulatory challenges, ethical considerations, and pharmacomicrobiomics are also highlighted to shed light on future development of tailored microbiome-based therapeutics.

Alzheimer DataLENS: An Open Data Analytics Portal for Alzheimer's Disease Research.

Recent Alzheimer's disease (AD) discoveries are increasingly based on studies from a variety of omics technologies on large cohorts. Currently, there is no easily accessible resource for neuroscientists to browse, query, and visualize these complex datasets in a harmonized manner. Create an online portal of public omics datasets for AD research. We developed Alzheimer DataLENS, a web-based portal, using the R Shiny platform to query and visualize publicly available transcriptomics and genetics studies of AD on human cohorts. To ensure consistent representation of AD findings, all datasets were processed through a uniform bioinformatics pipeline. Alzheimer DataLENS currently houses 2 single-nucleus RNA sequencing datasets, over 30 bulk RNA sequencing datasets from 19 brain regions and 3 cohorts, and 2 genome-wide association studies (GWAS). Available visualizations for single-nucleus data include bubble plots, heatmaps, and UMAP plots; for bulk expression data include box plots and heatmaps; for pathways include protein-protein interaction network plots; and for GWAS results include Manhattan plots. Alzheimer DataLENS also links to two other knowledge resources: the AD Progression Atlas and the Astrocyte Atlas. Alzheimer DataLENS is a valuable resource for investigators to quickly and systematically explore omics datasets and is freely accessible at https://alzdatalens.partners.org.

The Tree of Life eDNA metabarcoding reveals a similar taxonomic richness but dissimilar evolutionary lineages between seaports and marine reserves.

Coastal areas host a major part of marine biodiversity but are seriously threatened by ever-increasing human pressures. Transforming natural coastlines into urban seascapes through habitat artificialization may result in loss of biodiversity and key ecosystem functions. Yet, the extent to which seaports differ from nearby natural habitats and marine reserves across the whole Tree of Life is still unknown. This study aimed to assess the level of α and β-diversity between seaports and reserves, and whether these biodiversity patterns are conserved across taxa and evolutionary lineages. For that, we used environmental DNA (eDNA) metabarcoding to survey six seaports on the French Mediterranean coast and four strictly no-take marine reserves nearby. By targeting four different groups-prokaryotes, eukaryotes, metazoans and fish-with appropriate markers, we provide a holistic view of biodiversity on contrasted habitats. In the absence of comprehensive reference databases, we used bioinformatic pipelines to gather similar sequences into molecular operational taxonomic units (MOTUs). In contrast to our expectations, we obtained no difference in MOTU richness (α-diversity) between habitats except for prokaryotes and threatened fishes with higher diversity in reserves than in seaports. However, we observed a marked dissimilarity (β-diversity) between seaports and reserves for all taxa. Surprisingly, this biodiversity signature of seaports was preserved across the Tree of Life, up to the order. This result reveals that seaports and nearby marine reserves share few taxa and evolutionary lineages along urbanized coasts and suggests major differences in terms of ecosystem functioning between both habitats.

Abstract PO1-07-10: Blood Based Early Cancer Detection Assay

Abstract Background: Breast cancer screening programs utilizing mammography have been shown to be highly effective in identifying breast cancer in women over the age of 40. High breast density is an independent risk factor for breast cancer and makes mammograms more difficult to interpret, decreasing their sensitivity. In the spring of 2023, the FDA, who certifies all mammography facilities under the Mammography Quality Standards Act, updated its regulations to require that breast density status be reported to all individuals receiving a mammogram. The new guidelines now require individuals with dense breast tissue be notified of this status. The guidelines also recommend these women discuss additional screening options with their healthcare providers1. These additional screening options may include breast tomosynthesis, breast MRI, breast ultrasound, and/or molecular breast imaging. Many of these options require additional exposure to radiation, are expensive, and are not equitably available across the country. In addition, they all require a follow-up appointment. Compliance can be challenging given the top barriers to mammography cited include the need for transportation, child-care, and the ability to take time off from work2. Genece Health is developing a simpler and less expensive screening solution that identifies the presence of early to late-stage breast cancer using cfDNA from a single blood draw. The Genece Health assay utilizes an algorithm that leverages Artificial Intelligence and Machine Learning to analyze fragment size and end motif patterns in cfDNA as well as regional mutational density to detect presence of ctDNA originating from breast cancer. This algorithm provides highly sensitive and specific results in a preliminary data set. Methods: The preliminary data set, presented herein, is a cohort of over 50 retrospective breast cancer plasma samples and over 100 presumed normal samples. The breast cancer samples were collected at all stages of progression, from stage 0, or ductal carcinoma in situ (DCIS), through stage IV. The majority ( >50%) were from stage I breast cancer. 400 µL of double spun plasma, collected in Streck BCT devices, was processed to purify and isolate cfDNA. cfDNA was used to create WGS libraries that were sequenced on a NovaSeq 6000. Sequence data were analyzed using a bioinformatics pipeline that yields an ensemble probability that correlates to the presence or absence of ctDNA from breast cancer. Results: The Genece Health assay and algorithm performed with a specificity greater than 85%. With this specificity, the assay had a sensitivity greater than 85% in samples from stages II to IV and a slightly lower sensitivity in stage 0 and I samples. Follow-up analyses were conducted to stratify performance based on breast cancer type (e.g. invasive ductal carcinoma vs invasive lobular carcinoma) and HR, PR, and HER2 status (e.g. HER2-negatives vs HER2-positives). Conclusions: The presented preliminary data indicate that the Genece Health technology can be leveraged as a complement to mammography in indications, such as dense breast tissue, where there is an unmet need for an easy and cost-effective way to monitor for breast cancer. The ability to have a blood-based test to complement mammography could reduce the access barriers most cited by females in the United States. Follow-up studies with greater numbers of samples and additional training and optimizations of the algorithm will yield performance improvements that allow the assay to detect all types and stages of breast cancer.

Abstract PO4-06-08: ZP4 AS A NOVEL TARGET FOR CAR T CELL THERAPY IN TRIPLE NEGATIVE BREAST CANCER

Abstract Triple negative breast cancer (TNBC) has the worst prognosis of BC subtypes, largely due to lack of approved targeted therapies. Chimeric antigen receptor (CAR) T cells have demonstrated great success in certain hematological malignancies; however, in the treatment of solid cancers, CAR T cells are faced with a variety of obstacles that limit their efficacy, including on-target/off-tumor toxicity. To minimize these toxicities, the ideal CAR T cell target must be overexpressed by the tumor and absent from vital organs. Cancer/germline (CG) antigens satisfy this need, as their expression is restricted to male or female germ cells. Using a bioinformatic pipeline to identify novel CG antigens expressed in TNBC and other solid cancers, we have identified zona pellucida glycoprotein 4 (ZP4) as a candidate CG antigen target for CAR T cell therapy. This protein is a component of the human zona pellucida matrix, an extracellular structure that surrounds the oocyte and functions in folliculogenesis, species-specific fertilization, and early development. We have identified ZP4 expression in approximately 10% of TNBC cases from available RNAseq and proteomic databases and have confirmed ZP4 expression in several TNBC PDX models. The overall purpose of this study is to redirect T cells against ZP4 by engineering and validating a second generation ZP4-specific CAR. We have generated a library of monoclonal antibody (mAb) candidates against the extracellular portion of human ZP4. Antibody clones were screened, and their specificity validated via ELISA and flow cytometry, and the three strongest binders (z108, z128, and z164) were selected for further investigation. By IHC, we confirmed that the ZP4 mAb clones stained the area surrounding normal oocytes and did not show binding to any of the 23 normal tissues screened. The variable regions of the antibody heavy and light chains were sequenced using 5’RACE and used to assemble second generation CAR constructs composed of the variable heavy and light chain fragments separated by a linker, a CH2/CH3 hinge domain, a CD28 transmembrane domain, a CD28 co-stimulatory domain, and the CD3z signaling domain. Activated T cells transduced with retroviral supernatant express the ZP4 CAR constructs at high levels. While all ZP4 CAR T cells demonstrate antigen-specific cytotoxic killing of ZP4+ target tumor cells in short-term in vitro assays, z128 ZP4 CAR T cells demonstrate superior persistence and efficacy in long-term repeat tumor challenge in vitro assays and orthotopic in vivo mouse models. In summary, ZP4 is a promising target for TNBC and we have successfully engineered ZP4 specific CAR T cells. ZP4 CAR T cells effectively target and kill ZP4+ cells in in vitro cytotoxicity assays but perform differently in repeat tumor challenge assays and in vivo. Future studies will elucidate the precise differences between our three candidate CAR constructs and further test the effector function, trafficking, proliferation, and persistence of z128 ZP4 CAR T cells in vivo using ZP4+ PDX models. This work has exciting potential to bring a novel CAR T cell therapy to patients with TNBC, without concerns for on-target off-tumor toxicity. Citation Format: Lauren Somes, Jonathan Lei, Paul Shafer, Xinpei Yi, Diego Chamorro, Emily Madaras, Michael Lewis, Bing Zhang, Valentina Hoyos. ZP4 AS A NOVEL TARGET FOR CAR T CELL THERAPY IN TRIPLE NEGATIVE BREAST CANCER [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-06-08.

Abstract PS06-06: Analysis of ctDNA for the detection of minimal residual disease (MRD) using a tissue-free, multiomic assay in patients with early-stage breast cancer

Abstract Background: The detection of ctDNA in patients with early-stage breast cancer after completion of adjuvant therapy is associated with a high risk of recurrence. Current clinical guidelines do not recommend routine screening for metastatic disease unless there are clinical signs and symptoms in patients who completed adjuvant therapy. However, ctDNA may serve as an early biomarker of recurrence which may allow effective identification of patients with asymptomatic distant metastases or molecular relapse only, who could benefit from early treatment intervention. Herein, we utilized a tissue-free, multiomic assay for the sensitive and specific detection of MRD in patients with early-stage breast cancer. Methods: Plasma samples were collected from patients with stage I-III breast cancer who were enrolled in the SUCCESS-A phase 3 clinical trial (NCT02181101) between 2006 and 2007. All patients received adjuvant chemotherapy +/- endocrine therapy and/or anti-HER2 therapy. Samples were collected approximately two years after completion of adjuvant chemotherapy, and plasma samples selected for analysis were from patients without evidence of disease recurrence prior to sample collection. Presence of MRD was assessed using Guardant Reveal powered by Infinity, which evaluates the epigenomic signals associated with cancer versus normal DNA for the detection of ctDNA. Samples with the presence of ctDNA are characterized for somatic alterations with common sources of interference such as clonal hematopoiesis excluded. An analytically validated bioinformatics pipeline was used for the detection of breast cancer ctDNA. Samples were analyzed blinded to the clinical data. Median survival times were estimated using the Kaplan-Meier method and hazard ratios were calculated based on univariable cox regression models. Results: A total of 311 plasma samples from 311 patients were evaluable. ctDNA was detected in 34% (13/38) of patients who subsequently developed distant recurrence and in none (0/7) of the patients who had local or contralateral breast cancer recurrence. ctDNA was detected in 60% (9/15) of samples that were collected within one year before recurrence. In the ctDNA detected samples from patients who had disease recurrence, the median time from sample collection to recurrence was 7.9 months (range, 1.4-28.6 months). ctDNA was detected in 6 patients who did not have a documented disease recurrence, resulting in a specificity of 97.7% (260/266). In the overall cohort, ctDNA detection was prognostic for recurrence-free survival (RFS; HR 11.0, 95% CI 2.28-53.6; p< 0.0001), distant recurrence-free survival (D-RFS; HR 13.7, 95% CI 2.52-74.9; p< 0.0001), and overall survival (OS; HR 17.4, 95% CI 1.33-227; p< 0.0001). Conclusion: Detection of ctDNA after adjuvant chemotherapy was highly prognostic and demonstrated high specificity in an early-stage breast cancer cohort. Larger, prospective studies are needed to confirm the prognostic value of ctDNA in the post-treatment setting and assess the clinical utility of MRD detection in this population. Citation Format: Wolfgang Janni, Thomas Friedl, Brigitte Rack, Peter A. Fasching, Andreas Hartkopf, Hans Tesch, Ralf Lorenz, Georg Heinrich, Jens-Uwe Blohmer, Tanja Fehm, Volkmar Müller, Andreas Schneeweiss, Matthias Beckmann, Matthias Ruebner, Nadia Harbeck, Klaus Pantel, Derek Dustin, Mingyang Cai. Analysis of ctDNA for the detection of minimal residual disease (MRD) using a tissue-free, multiomic assay in patients with early-stage breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS06-06.

Development of a high dimensional imaging mass cytometry panel to investigate spatial organization of tissue microenvironment in formalin-fixed archival clinical tissues

To decipher the interactions between various components of the tumor microenvironment (TME) and tumor cells in a preserved spatial context, a multiparametric approach is essential. In this pursuit, imaging mass cytometry (IMC) emerges as a valuable tool, capable of concurrently analyzing up to 40 parameters at subcellular resolution. In this study, a set of antibodies was selected to spatially resolve multiple cell types and TME elements, including a comprehensive panel targeted at dissecting the heterogeneity of cancer-associated fibroblasts (CAF), a pivotal TME component. This antibody panel was standardized and optimized using formalin-fixed paraffin-embedded tissue (FFPE) samples from different organs/lesions known to express the markers of interest. The final composition of the antibody panel was determined based on the performance of conjugated antibodies in both immunohistochemistry (IHC) and IMC. Tissue images were segmented employing the Steinbock framework. Unsupervised clustering of single-cell data was carried out using a bioinformatics pipeline developed in R program. This paper provides a detailed description of the staining procedure and analysis workflow. Subsequently, the panel underwent validation on clinical FFPE samples from head and neck squamous cell carcinoma (HNSCC). The panel and bioinformatics pipeline established here proved to be robust in characterizing different TME components of HNSCC while maintaining a high degree of spatial detail. The platform we describe shows promise for understanding the clinical implications of TMA heterogeneity in large patient cohorts with FFPE tissues available in diagnostic biobanks worldwide.

Advancing metagenome-assembled genome-based pathogen identification: unraveling the power of long-read assembly algorithms in Oxford Nanopore sequencing.

Oxford Nanopore sequencing is one of the high-throughput sequencing technologies that facilitates the reconstruction of metagenome-assembled genomes (MAGs). This study aimed to assess the potential of long-read assembly algorithms in Oxford Nanopore sequencing to enhance the MAG-based identification of bacterial pathogens using both simulated and mock communities. Simulated communities were generated to mimic those on fresh spinach and in surface water. Long reads were produced using R9.4.1+SQK-LSK109 and R10.4 + SQK-LSK112, with 0.5, 1, and 2 million reads. The simulated bacterial communities included multidrug-resistant Salmonella enterica serotypes Heidelberg, Montevideo, and Typhimurium in the fresh spinach community individually or in combination, as well as multidrug-resistant Pseudomonas aeruginosa in the surface water community. Real data sets of the ZymoBIOMICS HMW DNA Standard were also studied. A bioinformatic pipeline (MAGenie, freely available at https://github.com/jackchen129/MAGenie) that combines metagenome assembly, taxonomic classification, and sequence extraction was developed to reconstruct draft MAGs from metagenome assemblies. Five assemblers were evaluated based on a series of genomic analyses. Overall, Flye outperformed the other assemblers, followed by Shasta, Raven, and Unicycler, while Canu performed least effectively. In some instances, the extracted sequences resulted in draft MAGs and provided the locations and structures of antimicrobial resistance genes and mobile genetic elements. Our study showcases the viability of utilizing the extracted sequences for precise phylogenetic inference, as demonstrated by the consistent alignment of phylogenetic topology between the reference genome and the extracted sequences. R9.4.1+SQK-LSK109 was more effective in most cases than R10.4+SQK-LSK112, and greater sequencing depths generally led to more accurate results.IMPORTANCEBy examining diverse bacterial communities, particularly those housing multiple Salmonella enterica serotypes, this study holds significance in uncovering the potential of long-read assembly algorithms to improve metagenome-assembled genome (MAG)-based pathogen identification through Oxford Nanopore sequencing. Our research demonstrates that long-read assembly stands out as a promising avenue for boosting precision in MAG-based pathogen identification, thus advancing the development of more robust surveillance measures. The findings also support ongoing endeavors to fine-tune a bioinformatic pipeline for accurate pathogen identification within complex metagenomic samples.

Performance of amplicon and capture based next-generation sequencing approaches for the epidemiological surveillance of Omicron SARS-CoV-2 and other variants of concern.

To control the SARS-CoV-2 pandemic, healthcare systems have focused on ramping up their capacity for epidemiological surveillance through viral whole genome sequencing. In this paper, we tested the performance of two protocols of SARS-CoV-2 nucleic acid enrichment, an amplicon enrichment using different versions of the ARTIC primer panel and a hybrid-capture method using KAPA RNA Hypercap. We focused on the challenge of the Omicron variant sequencing, the advantages of automated library preparation and the influence of the bioinformatic analysis in the final consensus sequence. All 94 samples were sequenced using Illumina iSeq 100 and analysed with two bioinformatic pipelines: a custom-made pipeline and an Illumina-owned pipeline. We were unsuccessful in sequencing six samples using the capture enrichment due to low reads. On the other hand, amplicon dropout and mispriming caused the loss of mutation G21987A and the erroneous addition of mutation T15521A respectively using amplicon enrichment. Overall, we found high sequence agreement regardless of method of enrichment, bioinformatic pipeline or the use of automation for library preparation in eight different SARS-CoV-2 variants. Automation and the use of a simple app for bioinformatic analysis can simplify the genotyping process, making it available for more diagnostic facilities and increasing global vigilance.

Chromosomal and plasmid-encoded virulence and multidrug resistance of Escherichia coli ST58/24 infecting a 2-year-old sickle cell patient with sepsis in Kampala Uganda, East Africa

Sepsis and drug resistance represent a complex of the most common global causes of mortality in intensive care units (ICUs) especially among patients with comorbidities. Extraintestinal pathogenic Escherichia coli (ExPEC) strains are highly implicated in systemic infections, with multidrug resistance exacerbating the risk of chronic conditions and patient mortality. The diversity of virulence and evolution of multidrug resistance are yet to be fully deciphered. In this work, we aimed at unveiling the pathogens and their genomic determinants of virulence and drug resistance relevant to increased sepsis in a sickle cell child admitted to ICU. From a rectal swab, we isolated a strain of E. coli from the patient and phenotypically tested it against a panel of selected beta lactams, fluoroquinolones, macrolides, aminoglycosides and colistin. We then sequenced the entire genome and integrated multiple bioinformatic pipelines to divulge the virulence and multidrug resistance profiles of the isolate. Our results revealed that the isolate belongs to the sequence type (ST) 58/24, which (ST58), is a known ExPEC. With the use of PathogenFinder, we were able to confirm that this isolate is a human pathogen (p = 0.936). The assembled chromosome and two plasmids encode virulence factors related to capsule (antiphagocytosis), serum survival and resistance, type 6 secretion system (T6SS), multiple siderophores (iron acquisition), and biosynthetic gene clusters for polyketides and nonribosomal peptides exhibiting host cell damaging activity in silico. The genome also harbors multidrug resistance genotypes including extended spectrum beta lactamase (ESBL) genes such as blaTEM-1A/B, sulfonamide resistance genes sul1/2, fluoroquinolone resistance genes dfrA5 and nonsynonymous mutations of the gene pmrB, conferring intrinsic colistin resistance. Conclusively, this pathogen holds the potential to cause systemic infection and might exacerbate sickle cell anemia in the patient. The virulence and multidrug resistance profiles are encoded by both the chromosome and plasmids. Genomic surveillance of pathogens with multidrug resistance among patients with commodities is crucial for effective disease management.

OmicNavigator: open-source software for the exploration, visualization, and archival of omic studies

BackgroundThe results of high-throughput biology (‘omic’) experiments provide insight into biological mechanisms but can be challenging to explore, archive and share. The scale of these challenges continues to grow as omic research volume expands and multiple analytical technologies, bioinformatic pipelines, and visualization preferences have emerged. Multiple software applications exist that support omic study exploration and/or archival. However, an opportunity remains for open-source software that can archive and present the results of omic analyses with broad accommodation of study-specific analytical approaches and visualizations with useful exploration features.ResultsWe present OmicNavigator, an R package for the archival, visualization and interactive exploration of omic studies. OmicNavigator enables bioinformaticians to create web applications that interactively display their custom visualizations and analysis results linked with app-derived analytical tools, graphics, and tables. Studies created with OmicNavigator can be viewed within an interactive R session or hosted on a server for shared access.ConclusionsOmicNavigator can be found at https://github.com/abbvie-external/OmicNavigator