Annotation of nuclear lncRNAs based on chromatin interactions.

The human genome is pervasively transcribed and produces a wide variety of long non-coding RNAs (lncRNAs), constituting the majority of transcripts across human cell types. Some specific nuclear lncRNAs have been shown to be important regulatory components acting locally. As RNA-chromatin interaction and Hi-C chromatin conformation data showed that chromatin interactions of nuclear lncRNAs are determined by the local chromatin 3D conformation, we used Hi-C data to identify potential target genes of lncRNAs. RNA-protein interaction data suggested that nuclear lncRNAs act as scaffolds to recruit regulatory proteins to target promoters and enhancers. Nuclear lncRNAs may therefore play a role in directing regulatory factors to locations spatially close to the lncRNA gene. We provide the analysis results through an interactive visualization web portal at https://fantom.gsc.riken.jp/zenbu/reports/#F6_3D_lncRNA.

Understanding metric-related pitfalls in image analysis validation.

Validation metrics are key for tracking scientific progress and bridging the current chasm between artificial intelligence research and its translation into practice. However, increasing evidence shows that, particularly in image analysis, metrics are often chosen inadequately. Although taking into account the individual strengths, weaknesses and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multistage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides a reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. Although focused on biomedical image analysis, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. The work serves to enhance global comprehension of a key topic in image analysis validation.

Metrics reloaded: recommendations for image analysis validation.

Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. In biomedical image analysis, chosen performance metrics often do not reflect the domain interest, and thus fail to adequately measure scientific progress and hinder translation of ML techniques into practice. To overcome this, we created Metrics Reloaded, a comprehensive framework guiding researchers in the problem-aware selection of metrics. Developed by a large international consortium in a multistage Delphi process, it is based on the novel concept of a problem fingerprint-a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), dataset and algorithm output. On the basis of the problem fingerprint, users are guided through the process of choosing and applying appropriate validation metrics while being made aware of potential pitfalls. Metrics Reloaded targets image analysis problems that can be interpreted as classification tasks at image, object or pixel level, namely image-level classification, object detection, semantic segmentation and instance segmentation tasks. To improve the user experience, we implemented the framework in the Metrics Reloaded online tool. Following the convergence of ML methodology across application domains, Metrics Reloaded fosters the convergence of validation methodology. Its applicability is demonstrated for various biomedical use cases.

SWATH-MS as a strategy for CHO host cell protein identification and quantification supporting the characterization of mAb purification platforms.

Host cell proteins (HCPs) are process-related impurities expressed by the host cells during biotherapeutics' manufacturing, such as monoclonal antibodies (mAbs). Some challenging HCPs evade clearance during the downstream processing and can be co-purified with the molecule of interest, which may impact product stability, efficacy, and safety. Therefore, HCP content is a critical quality attribute to monitor and quantify across the bioprocess. Here we explored a mass spectrometry (MS)-based proteomics tool, the sequential window acquisition of all theoretical fragment-ion spectra (SWATH) strategy, as an orthogonal method to traditional ELISA. The SWATH workflow was applied for high-throughput individual HCP identification and quantification, supporting characterization of a mAb purification platform. The design space of HCP clearance of two polishing resins was evaluated through a design of experiment study. Absolute quantification of high-risk HCPs was achieved (reaching 1.8 and 4.2 ppm limits of quantification, for HCP A and B respectively) using HCP-specific synthetic heavy labeled peptide calibration curves. Profiling of other HCPs was also possible using an average calibration curve (using labeled peptides from different HCPs). The SWATH approach is a powerful tool for HCP assessment during bioprocess development enabling simultaneous monitoring and quantification of different individual HCPs and improving process understanding of their clearance.

Modeling methyl-sensitive transcription factor motifs with an expanded epigenetic alphabet.

BACKGROUND: Transcription factors bind DNA in specific sequence contexts. In addition to distinguishing one nucleobase from another, some transcription factors can distinguish between unmodified and modified bases. Current models of transcription factor binding tend not to take DNA modifications into account, while the recent few that do often have limitations. This makes a comprehensive and accurate profiling of transcription factor affinities difficult. RESULTS: Here, we develop methods to identify transcription factor binding sites in modified DNA. Our models expand the standard A/C/G/T DNA alphabet to include cytosine modifications. We develop Cytomod to create modified genomic sequences and we also enhance the MEME Suite, adding the capacity to handle custom alphabets. We adapt the well-established position weight matrix (PWM) model of transcription factor binding affinity to this expanded DNA alphabet. Using these methods, we identify modification-sensitive transcription factor binding motifs. We confirm established binding preferences, such as the preference of ZFP57 and C/EBPß for methylated motifs and the preference of c-Myc for unmethylated E-box motifs. CONCLUSIONS: Using known binding preferences to tune model parameters, we discover novel modified motifs for a wide array of transcription factors. Finally, we validate our binding preference predictions for OCT4 using cleavage under targets and release using nuclease (CUT&RUN) experiments across conventional, methylation-, and hydroxymethylation-enriched sequences. Our approach readily extends to other DNA modifications. As more genome-wide single-base resolution modification data becomes available, we expect that our method will yield insights into altered transcription factor binding affinities across many different modifications.

Understanding metric-related pitfalls in image analysis validation.

Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation into practice. However, increasing evidence shows that particularly in image analysis, metrics are often chosen inadequately in relation to the underlying research problem. This could be attributed to a lack of accessibility of metric-related knowledge: While taking into account the individual strengths, weaknesses, and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multi-stage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides the first reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. Focusing on biomedical image analysis but with the potential of transfer to other fields, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. To facilitate comprehension, illustrations and specific examples accompany each pitfall. As a structured body of information accessible to researchers of all levels of expertise, this work enhances global comprehension of a key topic in image analysis validation.

Measurement of Blood Dilution during Lancet-Free Blood Sampling.

In this paper, we report on a fluorescent and colorimetric system for measuring the dilution of capillary blood released by a needle-free jet injector. Jet injection uses a high-speed liquid jet to penetrate tissue, and in the process can release capillary blood that can be collected for performing blood tests. In this way, blood sampling can be performed without the use of a lancet. However, any injectate that mixes with the collected blood dilutes the sample and may significantly impact subsequent analyses. By adding the fluorescent marker indocyanine green to the injected liquid, the fraction of injectate mixed into the collected blood can be measured. The incorporation of colorimetry allows our system to also correct for the impact of hematocrit on fluorescence. The results from this system show that it can determine the dilution of blood that has been diluted by up to 10 %, the upper limit of dilution typically observed in lancet-free blood sampling via jet injection.Clinical Relevance- Blood samples can be collected by jet injection without significant dilution, avoiding the need for lancing.

Identification of Mispairing Omic Signatures in Chinese Hamster Ovary (CHO) Cells Producing a Tri-Specific Antibody.

Monoclonal antibody-based therapy has shown efficacy against cancer, autoimmune, infectious, and inflammatory diseases. Multispecific antibodies (MsAbs), including trispecifics (tsAbs), offer enhanced therapeutic potential by targeting different epitopes. However, when co-expressed from three or more different polypeptide chains, MsAb production can lead to incorrect chain assembly and co-production of mispaired species with impaired biological activity. Moreover, mispairing carries significant challenges for downstream purification, decreasing yields and increasing the cost of bioprocess development. In this study, quantitative transcriptomics and proteomics analyses were employed to investigate which signaling pathways correlated with low and high mispairing clone signatures. Gene and protein expression profiles of Chinese hamster ovary (CHO) clones producing an tsAb were analyzed in the exponential growth and stationary (tsAb production) phase of fed-batch culture. Functional analysis revealed activated endoplasmic reticulum stress in high mispairing clones in both culture phases, while low mispairing clones exhibited expression profiles indicative of activated protein translation, as well as higher endocytosis and target protein degradation, suggesting the clearance of unfolded proteins through ubiquitin-mediated mechanisms. In addition, through transcriptomic profiling, we identified a group of genes that have the potential to be used as a biomarker panel tool for identifying high mispairing levels in the early stages of bioprocess development.

Epigenetic reprogramming of a distal developmental enhancer cluster drives SOX2 overexpression in breast and lung adenocarcinoma.

Enhancer reprogramming has been proposed as a key source of transcriptional dysregulation during tumorigenesis, but the molecular mechanisms underlying this process remain unclear. Here, we identify an enhancer cluster required for normal development that is aberrantly activated in breast and lung adenocarcinoma. Deletion of the SRR124-134 cluster disrupts expression of the SOX2 oncogene, dysregulates genome-wide transcription and chromatin accessibility and reduces the ability of cancer cells to form colonies in vitro. Analysis of primary tumors reveals a correlation between chromatin accessibility at this cluster and SOX2 overexpression in breast and lung cancer patients. We demonstrate that FOXA1 is an activator and NFIB is a repressor of SRR124-134 activity and SOX2 transcription in cancer cells, revealing a co-opting of the regulatory mechanisms involved in early development. Notably, we show that the conserved SRR124 and SRR134 regions are essential during mouse development, where homozygous deletion results in the lethal failure of esophageal-tracheal separation. These findings provide insights into how developmental enhancers can be reprogrammed during tumorigenesis and underscore the importance of understanding enhancer dynamics during development and disease.

The manuscript by Abatti et al. shows that epigenetic reactivation of a pair of distal enhancers that drive Sox2 expression during development (to permit separation of the esophagus and trachea) is responsible for the tumor-promoting re-expression of SOX2 in breast and lung tumors. Intriguingly, the same transcription factors that act on the enhancers during development to either activate or repress them (i.e. FOXA1 and NFIB, respectively) are also required for altering chromatin accessibility of the enhancers and SOX2 transcription in breast and lung cancer cells. With their work, the authors unravel the exact mechanism of how developmentally active enhancers become repurposed in a tumor context and show the relevance of this repurposing event for cancer.

Exploring the merits of research performance measures that comply with the San Francisco Declaration on Research Assessment and strategies to overcome barriers of adoption: qualitative interviews with administrators and researchers.

BACKGROUND: In prior research, we identified and prioritized ten measures to assess research performance that comply with the San Francisco Declaration on Research Assessment, a principle adopted worldwide that discourages metrics-based assessment. Given the shift away from assessment based on Journal Impact Factor, we explored potential barriers to implementing and adopting the prioritized measures. METHODS: We identified administrators and researchers across six research institutes, conducted telephone interviews with consenting participants, and used qualitative description and inductive content analysis to derive themes. RESULTS: We interviewed 18 participants: 6 administrators (research institute business managers and directors) and 12 researchers (7 on appointment committees) who varied by career stage (2 early, 5 mid, 5 late). Participants appreciated that the measures were similar to those currently in use, comprehensive, relevant across disciplines, and generated using a rigorous process. They also said the reporting template was easy to understand and use. In contrast, a few administrators thought the measures were not relevant across disciplines. A few participants said it would be time-consuming and difficult to prepare narratives when reporting the measures, and several thought that it would be difficult to objectively evaluate researchers from a different discipline without considerable effort to read their work. Strategies viewed as necessary to overcome barriers and support implementation of the measures included high-level endorsement of the measures, an official launch accompanied by a multi-pronged communication strategy, training for both researchers and evaluators, administrative support or automated reporting for researchers, guidance for evaluators, and sharing of approaches across research institutes. CONCLUSIONS: While participants identified many strengths of the measures, they also identified a few limitations and offered corresponding strategies to address the barriers that we will apply at our organization. Ongoing work is needed to develop a framework to help evaluators translate the measures into an overall assessment. Given little prior research that identified research assessment measures and strategies to support adoption of those measures, this research may be of interest to other organizations that assess the quality and impact of research.

Human papillomavirus integration transforms chromatin to drive oncogenesis.

BACKGROUND: Human papillomavirus (HPV) drives almost all cervical cancers and up to 70% of head and neck cancers. Frequent integration into the host genome occurs predominantly in tumorigenic types of HPV. We hypothesize that changes in chromatin state at the location of integration can result in changes in gene expression that contribute to the tumorigenicity of HPV. RESULTS: We find that viral integration events often occur along with changes in chromatin state and expression of genes near the integration site. We investigate whether introduction of new transcription factor binding sites due to HPV integration could invoke these changes. Some regions within the HPV genome, particularly the position of a conserved CTCF binding site, show enriched chromatin accessibility signal. ChIP-seq reveals that the conserved CTCF binding site within the HPV genome binds CTCF in 4 HPV+ cancer cell lines. Significant changes in CTCF binding pattern and increases in chromatin accessibility occur exclusively within 100 kbp of HPV integration sites. The chromatin changes co-occur with out-sized changes in transcription and alternative splicing of local genes. Analysis of The Cancer Genome Atlas (TCGA) HPV+ tumors indicates that HPV integration upregulates genes which have significantly higher essentiality scores compared to randomly selected upregulated genes from the same tumors. CONCLUSIONS: Our results suggest that introduction of a new CTCF binding site due to HPV integration reorganizes chromatin state and upregulates genes essential for tumor viability in some HPV+ tumors. These findings emphasize a newly recognized role of HPV integration in oncogenesis.

DORA-compliant measures of research quality and impact to assess the performance of researchers in biomedical institutions: Review of published research, international best practice and Delphi survey.

OBJECTIVE: The San Francisco Declaration on Research Assessment (DORA) advocates for assessing biomedical research quality and impact, yet academic organizations continue to employ traditional measures such as Journal Impact Factor. We aimed to identify and prioritize measures for assessing research quality and impact. METHODS: We conducted a review of published and grey literature to identify measures of research quality and impact, which we included in an online survey. We assembled a panel of researchers and research leaders, and conducted a two-round Delphi survey to prioritize measures rated as high (rated 6 or 7 by ≥ 80% of respondents) or moderate (rated 6 or 7 by ≥ 50% of respondents) importance. RESULTS: We identified 50 measures organized in 8 domains: relevance of the research program, challenges to research program, or productivity, team/open science, funding, innovations, publications, other dissemination, and impact. Rating of measures by 44 panelists (60%) in Round One and 24 (55%) in Round Two of a Delphi survey resulted in consensus on the high importance of 5 measures: research advances existing knowledge, research plan is innovative, an independent body of research (or fundamental role) supported by peer-reviewed research funding, research outputs relevant to discipline, and quality of the content of publications. Five measures achieved consensus on moderate importance: challenges to research productivity, potential to improve health or healthcare, team science, collaboration, and recognition by professional societies or academic bodies. There was high congruence between researchers and research leaders across disciplines. CONCLUSIONS: Our work contributes to the field by identifying 10 DORA-compliant measures of research quality and impact, a more comprehensive and explicit set of measures than prior efforts. Research is needed to identify strategies to overcome barriers of use of DORA-compliant measures, and to "de-implement" traditional measures that do not uphold DORA principles yet are still in use.

Motif elucidation in ChIP-seq datasets with a knockout control.

Summary: Chromatin immunoprecipitation-sequencing is widely used to find transcription factor binding sites, but suffers from various sources of noise. Knocking out the target factor mitigates noise by acting as a negative control. Paired wild-type and knockout (KO) experiments can generate improved motifs but require optimal differential analysis. We introduce peaKO-a computational method to automatically optimize motif analyses with KO controls, which we compare to two other methods. PeaKO often improves elucidation of the target factor and highlights the benefits of KO controls, which far outperform input controls. Availability and implementation: PeaKO is freely available at https://peako.hoffmanlab.org. Contact: michael.hoffman@utoronto.ca.

Vacuum-Assisted Needle-Free Capillary Blood Sampling.

BACKGROUND: Poor glycemic management persists among people practicing insulin therapy in relation to type 1 and 2 diabetes despite a clear relationship with negative health outcomes. Skin penetration by jet injection has recently been shown as a viable method for inducing blood release from fingertips. This study examines the use of vacuum to enhance the volume of blood released and quantifies any dilution of the collected blood. METHODS: A single-blind crossover study involving 15 participants, each receiving four different interventions, was conducted wherein each participant served as their own control. Each participant experienced fingertip lancing and fingertip jet injection, both with and without applied vacuum. Participants were divided into three equal groups to explore different vacuum pressures. RESULTS: This study found that glucose concentration in blood collected under vacuum following jet injection and lancing were equivalent. We found that applying a 40 kPa vacuum following jet injection produced a 35-fold increase in the collected volume. We determined the limited extent to which the injectate dilutes blood collected following jet injection. The mean dilution of blood collected by jet injection was 5.5%. We show that jet injection is as acceptable to patients as lancing, while being equally suited for conducting glucose measurements. CONCLUSIONS: Vacuum significantly enhances the volume of capillary blood released from the fingertip without any difference in pain. The blood collected by jet injection with vacuum is equivalent to that from lancing for glucose measurement purposes.

Can vegetation be discretely classified in species-poor environments? Testing plant community concepts for vegetation monitoring on sub-Antarctic Marion Island.

The updating and rethinking of vegetation classifications is important for ecosystem monitoring in a rapidly changing world, where the distribution of vegetation is changing. The general assumption that discrete and persistent plant communities exist that can be monitored efficiently, is rarely tested before undertaking a classification. Marion Island (MI) is comprised of species-poor vegetation undergoing rapid environmental change. It presents a unique opportunity to test the ability to discretely classify species-poor vegetation with recently developed objective classification techniques and relate it to previous classifications. We classified vascular species data of 476 plots sampled across MI, using Ward hierarchical clustering, divisive analysis clustering, non-hierarchical kmeans and partitioning around medoids. Internal cluster validation was performed using silhouette widths, Dunn index, connectivity of clusters and gap statistic. Indicator species analyses were also conducted on the best performing clustering methods. We evaluated the outputs against previously classified units. Ward clustering performed the best, with the highest average silhouette width and Dunn index, as well as the lowest connectivity. The number of clusters differed amongst the clustering methods, but most validation measures, including for Ward clustering, indicated that two and three clusters are the best fit for the data. However, all classification methods produced weakly separated, highly connected clusters with low compactness and low fidelity and specificity to clusters. There was no particularly robust and effective classification outcome that could group plots into previously suggested vegetation units based on species composition alone. The relatively recent age (c. 450,000 years B.P.), glaciation history (last glacial maximum 34,500 years B.P.) and isolation of the sub-Antarctic islands may have hindered the development of strong vascular plant species assemblages with discrete boundaries. Discrete classification at the community-level using species composition may not be suitable in such species-poor environments. Species-level, rather than community-level, monitoring may thus be more appropriate in species-poor environments, aligning with continuum theory rather than community theory.

Community consensus on core open science practices to monitor in biomedicine.

The state of open science needs to be monitored to track changes over time and identify areas to create interventions to drive improvements. In order to monitor open science practices, they first need to be well defined and operationalized. To reach consensus on what open science practices to monitor at biomedical research institutions, we conducted a modified 3-round Delphi study. Participants were research administrators, researchers, specialists in dedicated open science roles, and librarians. In rounds 1 and 2, participants completed an online survey evaluating a set of potential open science practices, and for round 3, we hosted two half-day virtual meetings to discuss and vote on items that had not reached consensus. Ultimately, participants reached consensus on 19 open science practices. This core set of open science practices will form the foundation for institutional dashboards and may also be of value for the development of policy, education, and interventions.

Minimally invasive capillary blood sampling methods.

INTRODUCTION: Whole blood samples, including arterial, venous, and capillary blood, are regularly used for disease diagnosis and monitoring. The global Covid-19 pandemic has highlighted the need for a more resilient screening capacity. Minimally invasive sampling techniques, such as capillary blood sampling, are routinely used for point of care testing in the home healthcare setting and clinical settings such as the Intensive Care Unit with less pain and wounding than conventional venepuncture. AREAS COVERED: In this manuscript, we aim to provide a overview of state-of-the-art of techniques for obtaining samples of capillary blood. We first review both established and novel methods for releasing blood from capillaries in the skin. Next, we provide a comparison of different capillary blood sampling methods based on their mechanism, testing site, puncture size, cost, wound geometry, healing, and perceptions of pain. Finally, we overview established and new methods for enhancing capillary blood collection. EXPERT OPINION: We expect that microneedles will prove to be a preferred option for paediatric blood collection. The ability of microneedles to collect a capillary blood sample without pain will improve paediatric healthcare outcomes. Jet injection may prove to be a useful method for facilitating both blood collection and drug delivery.

Missed Opportunity: The Unseen Driver for Low Coronavirus Disease 2019 Vaccination Rates in Underserved Patients.

Background: Vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus have been available since December 2020. Vaccination rates among hospitalized patients at our institution remained low at approximately 40%, thus we sought to understand the drivers of vaccine hesitancy in our patient population. Methods: All unvaccinated adult patients admitted to our hospital were asked to participate in a survey to assess coronavirus disease 2019 (COVID-19) vaccine hesitancy. Updated vaccination status was collected at the end of the study. Results: Ninety-seven patients agreed to participate, 34% of which were SARS-CoV-2 positive based on results from polymerase chain reaction tests. Of the 64 participants eligible to receive the vaccine, 57.8% were agreeable but only 27% received the vaccine before discharge. Conclusion: Many patients are willing to receive the vaccine, and hospitalization provides a unique opportunity to interact with patients who have been otherwise unaware, unable, or unwilling to pursue vaccination outside of the hospital.