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Abstract Rapid and cost-efficient whole-genome sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019, is critical for understanding viral transmission dynamics. Here we show that using a new multiplexed set of primers in conjunction with the Oxford Nanopore Rapid Barcode library kit allows for faster, simpler, and less expensive SARS-CoV-2 genome sequencing. This primer set results in amplicons that exhibit lower levels of variation in coverage compared to other commonly used primer sets. Using five SARS-CoV-2 patient samples with Cq values between 20 and 31, we show that high-quality genomes can be generated with as few as 10 000 reads (∼5 Mbp of sequence data). We also show that mis-classification of barcodes, which may be more likely when using the Oxford Nanopore Rapid Barcode library prep, is unlikely to cause problems in variant calling. This method reduces the time from RNA to genome sequence by more than half compared to the more standard ligation-based Oxford Nanopore library preparation method at considerably lower costs.

microRNAs are small non-coding RNAs gaining interest for their potential roles as reliable biomarkers for the diagnosis and therapeutics of numerous pathologies, ranging from cancer to neurodegenerative or psychiatric disorders. Indeed, microRNAs are present in various accessible biofluids, including peripheral blood, and specific dysregulation of their expression may be associated with these different pathological conditions. microRNAs can be isolated from plasma or serum for sequencing with commercial kits. However, these two biofluids might exhibit some differences in their microRNA contents, due notably to the coagulation process occurring during serum collection. It remains unclear from previous studies and commercial recommendations which blood fraction is preferable. Because of the small amount of circulating microRNAs in a given blood volume, this question appears crucial for qualitative and quantitative optimization of microRNA profiling, especially in animal models used for investigating the pathophysiological relevancy of this approach. We therefore evaluated the efficiency of RNA isolation and microRNA levels from plasma and sera isolated from rats and humans, with a widely used extraction kit (QIAGEN miRNeasy), and assessed microRNA quality and quantity with high-throughput sequencing. Fewer reads with length corresponding to non-miRNAs sequences were observed in plasma than in serum, both from rats and humans. Moreover, rat plasma produced twice as many aligned reads compared to sera, as well as more aligned reads corresponding to microRNAs (84.6% against 38.7%), differences that were not find in human samples. Our results, therefore, clearly indicate that plasma should be preferred for miRNA investigations, particularly for translational studies.

Abstract Quantifying phenotypes is a common practice for addressing questions regarding morphological variation. The time dedicated to data acquisition can vary greatly depending on methods and on the required quantity of information. Optimizing digitization effort can be done either by pooling datasets among users, by automatizing data collection, or by reducing the number of measurements. Pooling datasets among users is not without risk since potential errors arising from multiple operators in data acquisition prevent combining morphometric datasets. We present an analytical workflow to estimate within and among operator biases and to assess whether morphometric datasets can be pooled. We show that pooling and sharing data requires careful examination of the errors occurring during data acquisition, that the choice of morphometric approach influences amount of error, and that in some cases pooling data should be avoided. The demonstration is based on a worked example (Sus scrofa teeth) using a combinations of 18 morphometric approaches and datasets for which we identified and quantified several potential sources of errors in the workflow. We show that it is possible to estimate the analytical power of a study using a small subset of data to select the best morphometric protocol and to optimize the number of variables necessary for analysis. In particular, we focus on semi-landmarks, which often produce an inflation of variables in contrast to the number of available observations use in statistical testing. We show how the workflow can be used for optimizing digitization efforts and provide recommendations for best practices in error management.

Abstract Dried blood spots (DBS) are widely utilized as part of universal newborn screening and as a means of transporting samples from field sites. We use DBS from African field sites to assess for rare maternal-fetal cell exchange during pregnancy known as microchimerism. We aimed to develop a protocol to maximize the quantity of high-quality genomic DNA (gDNA) extracted from DBS. The total gDNA yield obtained from control DBS utilizing a Qiagen-based protocol and a Chelex® 100 resin-based protocol was first compared. Variations of the Chelex® protocol were subsequently tested to develop an optimized protocol. The gDNA was quantified by qPCR targeting the human beta-globin gene. DNA yield for a given experimental condition was normalized to a Chelex® control performed on the same day, and the total yields were compared using a Student’s t-test. The control Chelex® protocol yielded 590% more DNA than the QIAamp® DNA Blood Mini Kit . The absolute efficiency of the control Chelex® protocol was 54%, compared to an absolute efficiency of 9% for the QIAamp® DNA Blood Mini Kit. Modification of the Chelex® protocol to include a second heat precipitation from the same DBS increased the gDNA yield by 29% (P < 0.001). Our optimized protocol including this modification increased the absolute efficiency of extraction to 68%. The gDNA extracted using the Chelex® protocol was stable through repeated freeze–thaw cycles. In a mock microchimerism experiment, rare donor alleles at a frequency of 10 in 100 000 could be identified in gDNA from DBS extracted using the optimized Chelex® protocol. Our findings may be of significance for a diverse range of applications that utilize DBS and require high-quality DNA, including newborn screening programs, pathogen and drug resistance screening from remote field sites, forensics, and rare allele detection.

Abstract Many studies have been made on nematodes, especially Caenorhabditis Elegans, which are used as a model organism. In many studies, the size of the nematode is important. This article describes a method of measuring the length, volume and surface area of nematodes from photographs. The method uses the imaging software ImageJ, which is in the public domain. Two macros are described. The first converts the images into binary form, and the second uses several built-in functions to measure the length of the worm and its diameter along its length. If it is assumed that the worm has a circular cross-section, then the volume and surface area of the nematode can be calculated. This is a cheap and easy technique.

Abstract Formalin-fixed, paraffin-embedded (FFPE) specimens have huge potential as source material in the field of human microbiome research. However, the effects of FFPE processing on bacterial DNA remain uncharacterized. Any effects are relevant for microbiome studies, where DNA template is often minimal and sequences studied are not limited to one genome. As such, we aimed to both characterize this FFPE-induced bacterial DNA damage and develop strategies to reduce and repair this damage. Our analyses indicate that bacterial FFPE DNA is highly fragmented, a poor template for PCR, crosslinked and bears sequence artefacts derived predominantly from oxidative DNA damage. Two strategies to reduce this damage were devised – an optimized decrosslinking procedure reducing sequence artefacts generated by high-temperature incubation, and secondly, an in vitro reconstitution of the base excision repair pathway. As evidenced by whole genome sequencing, treatment with these strategies significantly increased fragment length, reduced the appearance of sequence artefacts and improved the sequencing readability of bacterial and mammalian FFPE DNA. This study provides a new understanding of the condition of bacterial DNA in FFPE specimens and how this impacts downstream analyses, in addition to a strategy to improve the sequencing quality of bacterial and possibly mammalian FFPE DNA.

Abstract Targeted next-generation sequencing based on PCR amplification involves pooling of hundreds to thousands of primers, for preamplification and subsequent parallel single/multiplex PCR. It is often necessary to allocate the set of primers into subpools, a common issue being potential cross-hybridization. For smaller numbers of primers, pool division can be done manually using trial and error to minimize potential hybridization, but this becomes inefficient and time consuming with increasing numbers of primer pairs. We developed PrimerPooler that automates swapping of primer pairs between any user-defined number of subpools to obtain combinations with low-potential interactions. PrimerPooler performs inter-/intra-primer hybridization analysis to identify the adverse interactions, as well as simultaneous mapping of all primers onto a genome sequence in a single run without requiring a prior index of the genome. This allows detection of overlapping primer pairs and allocation of these primer pairs into separate subpools where tiling approaches are used. Using PrimerPooler, 1153 primer pairs were assigned to three preamplification pools (388, 389 and 376 primer pairs each), then 144 subpools of six- to nine-plex PCR for Fluidigm Access Array PCR, followed by Illumina MiSeq sequencing. With optimized experimental protocols, an average of 3269 reads was achieved for the targeted regions, with 95% of targets covered by at least 50 reads, the minimal depth of reads for confident variant calling. PrimerPooler provides a fast and highly efficient stratification of primer pairs for targeted enrichment, thus ensuring representative amplification of the targeted sequences. PrimerPooler is also able to analyse degenerate primers, and is thus also useful for microbiological identification and related target sequencing.

Abstract Single-cell RNA sequencing (scRNA-seq) of human primary tissues is a rapidly emerging tool for investigating human health and disease at the molecular level. However, optimal processing of solid tissues presents a number of technical and logistical challenges, especially for tissues that are only available at autopsy, which includes pancreatic islets, a tissue that is highly relevant to diabetes. To assess the possible effects of different sample preparation protocols on fresh islet samples, we performed a detailed comparison of scRNA-seq data generated with islets isolated from a human donor but processed according to four treatment strategies, including fixation and cryopreservation. We found significant and reproducible differences in the proportion of cell types identified, and more minor effects on cell-specific patterns of gene expression. Fresh islets from a second donor confirmed gene expression signatures of alpha and beta subclusters. These findings may well apply to other tissues, emphasizing the need for careful consideration when choosing processing methods, comparing results between different studies, and/or interpreting data in the context of multiple cell types from preserved tissue.

Abstract The combination of lentiviruses with techniques such as CRISPR-Cas9 has resulted in efficient and precise processes for targeted genome modification. An often-limiting aspect, however, is the efficiency of cell transduction. Low efficiencies with particular cell types and/or the high complexity of lentiviral libraries can cause insufficient representation. Here, we present a protocol that yielded substantial increases in transduction efficiency in various cell lines in comparison to several other procedures.

Abstract The environmental fate of many functional molecules that are produced on a large scale as precursors or as additives to specialty goods (plastics, fibers, construction materials, etc.), let alone those synthesized by the pharmaceutical industry, is generally unknown. Assessing their environmental fate is crucial when taking decisions on the manufacturing, handling, usage, and release of these substances, as is the evaluation of their toxicity in humans and other higher organisms. While this data are often hard to come by, the experimental data already available on the biodegradability and toxicity of many unusual compounds (including genuinely xenobiotic molecules) make it possible to develop machine learning systems to predict these features. As such, we have created a predictor of the “risk” associated with the use and release of any chemical. This new system merges computational methods to predict biodegradability with others that assess biological toxicity. The combined platform, named BiodegPred (https://sysbiol.cnb.csic.es/BiodegPred/), provides an informed prognosis of the chance a given molecule can eventually be catabolized in the biosphere, as well as of its eventual toxicity, all available through a simple web interface. While the platform described does not give much information about specific degradation kinetics or particular biodegradation pathways, BiodegPred has been instrumental in anticipating the probable behavior of a large number of new molecules (e.g. antiviral compounds) for which no biodegradation data previously existed.