The effect of low-abundance OTU filtering methods on the reliability and variability of microbial composition assessed by 16S rRNA amplicon sequencing

PCR amplicon sequencing may lead to detection of spurious operational taxonomic units (OTUs), inflating estimates of gut microbial diversity. There is no consensus in the analytical approach as to what filtering methods should be applied to remove low-abundance OTUs; moreover, few studies have investigated the reliability of OTU detection within replicates. Here, we investigated the reliability of OTU detection (% agreement in detecting OTU in triplicates) and accuracy of their quantification (assessed by coefficient of variation (CV)) in human stool specimens. Stool samples were collected from 12 participants 22-55 years old. We applied several methods for filtering low-abundance OTUs and determined their impact on alpha-diversity and beta-diversity metrics. The reliability of OTU detection without any filtering was only 44.1% (SE=0.9) but increased after filtering low-abundance OTUs. After filtering OTUs with <0.1% abundance in the dataset, the reliability increased to 87.7% (SE=0.6) but at the expense of removing 6.97% reads from the dataset. When filtering was based on individual sample, the reliability increased to 73.1% after filtering OTUs with <10 copies while removing only 1.12% of reads. High abundance OTUs (>10 copies in sample) had lower CV, indicating better accuracy of quantification than low-abundance OTUs. Excluding very low-abundance OTUs had a significant impact on alpha-diversity metrics sensitive to the presence of rare species (observed OTUs, Chao1) but had little impact on relative abundance of major phyla and families and alpha-diversity metrics accounting for both richness and evenness (Shannon, Inverse Simpson). To increase the reliability of microbial composition, we advise removing OTUs with <10 copies in individual samples, particularly in studies where only one subsample per specimen is available for analysis.

Comparison of long- and short-read metagenomic assembly for low-abundance species and resistance genes

Recent technological and computational advances have made metagenomic assembly a viable approach to achieving high-resolution views of complex microbial communities. In previous benchmarking, short-read (SR) metagenomic assemblers had the highest accuracy, long-read (LR) assemblers generated the most contiguous sequences and hybrid (HY) assemblers balanced length and accuracy. However, no assessments have specifically compared the performance of these assemblers on low-abundance species, which include clinically relevant organisms in the gut. We generated semi-synthetic LR and SR datasets by spiking small and increasing amounts of Escherichia coli isolate reads into fecal metagenomes and, using different assemblers, examined E. coli contigs and the presence of antibiotic resistance genes (ARGs). For ARG assembly, although SR assemblers recovered more ARGs with high accuracy, even at low coverages, LR assemblies allowed for the placement of ARGs within longer, E. coli-specific contigs, thus pinpointing their taxonomic origin. HY assemblies identified resistance genes with high accuracy and had lower contiguity than LR assemblies. Each assembler type's strengths were maintained even when our isolate was spiked in with a competing strain, which fragmented and reduced the accuracy of all assemblies. For strain characterization and determining gene context, LR assembly is optimal, while for base-accurate gene identification, SR assemblers outperform other options. HY assembly offers contiguity and base accuracy, but requires generating data on multiple platforms, and may suffer high misassembly rates when strain diversity exists. Our results highlight the trade-offs associated with each approach for recovering low-abundance taxa, and that the optimal approach is goal-dependent.

Where Have All the Spiders Gone? Observations of a Dramatic Population Density Decline in the Once Very Abundant Garden Spider, Araneus diadematus (Araneae: Araneidae), in the Swiss Midland

Aerial web-spinning spiders (including large orb-weavers), as a group, depend almost entirely on flying insects as a food source. The recent widespread loss of flying insects across large parts of western Europe, in terms of both diversity and biomass, can therefore be anticipated to have a drastic negative impact on the survival and abundance of this type of spider. To test the putative importance of such a hitherto neglected trophic cascade, a survey of population densities of the European garden spider Araneus diadematus—a large orb-weaving species—was conducted in the late summer of 2019 at twenty sites in the Swiss midland. The data from this survey were compared with published population densities for this species from the previous century. The study verified the above-mentioned hypothesis that this spider’s present-day overall mean population density has declined alarmingly to densities much lower than can be expected from normal population fluctuations (0.7% of the historical values). Review of other available records suggested that this pattern is widespread and not restricted to this region. In conclusion, the decline of this once so abundant spider in the Swiss midland is evidently revealing a bottom-up trophic cascade in response to the widespread loss of flying insect prey in recent decades.

Affinity enrichment for mass spectrometry: improving the yield of low abundance biomarkers

INTRODUCTION

Mass spectrometry (MS) is the premier tool for discovering novel disease-associated protein biomarkers. Unfortunately, when applied to complex body fluid samples, MS has poor sensitivity for the detection of low abundance biomarkers (≪10 ng/mL), derived directly from the diseased tissue cells or pathogens. Areas covered: Herein we discuss the strengths and drawbacks of technologies used to concentrate low abundance analytes in body fluids, with the aim to improve the effective sensitivity for MS discovery. Solvent removal by dry-down or dialysis, and immune-depletion of high abundance serum or plasma proteins, is shown to have disadvantages compared to positive selection of the candidate biomarkers by affinity enrichment. A theoretical analysis of affinity enrichment reveals that the yield for low abundance biomarkers is a direct function of the binding affinity (Association/Dissociation rates) used for biomarker capture. In addition, a high affinity capture pre processing step can effectively dissociate the candidate biomarker from partitioning with high abundance proteins such as albumin. Expert commentary: Properly designed high affinity capture materials can enrich the yield of low abundance (0.1-10 picograms/mL) candidate biomarkers for MS detection. Affinity capture and concentration, as an upfront step in sample preparation for MS, combined with MS advances in software and hardware that improve the resolution of the chromatographic separation can yield a transformative new class of low abundance biomarkers predicting disease risk or disease latency.

Pika Gut May Select for Rare but Diverse Environmental Bacteria

The composition of the mammalian gut bacterial communities can be influenced by the introduction of environmental bacteria in their respective habitats. However, there are no extensive studies examining the interactions between environmental bacteriome and gut bacteriome in wild mammals. Here, we explored the relationship between the gut bacterial communities of pika (Ochotona spp.) and the related environmental bacteria across host species and altitudinal sites using 16S rRNA gene sequencing. Plateau pikas (O. curzoniae) and Daurian pikas (O. daurica) were sampled at five different sites, and plant and soil samples were collected at each site as well. Our data indicated that Plateau pikas and Daurian pikas had distinct bacterial communities. The pika, plant and soil bacterial communities were also distinct. Very little overlap occurred in the pika core bacteria and the most abundant environmental bacteria. The shared OTUs between pikas and environments were present in the environment at relatively low abundance, whereas they were affiliated with diverse bacterial taxa. These results suggested that the pika gut may mainly select for low-abundance but diverse environmental bacteria in a host species-specific manner.

Improved proteome coverage by using high efficiency cysteinyl peptide enrichment: the human mammary epithelial cell proteome

Automated multidimensional capillary liquid chromatography-tandem mass spectrometry (LC-MS/MS) has been increasingly applied in various large scale proteome profiling efforts. However, comprehensive global proteome analysis remains technically challenging due to issues associated with sample complexity and dynamic range of protein abundances, which is particularly apparent in mammalian biological systems. We report here the application of a high efficiency cysteinyl peptide enrichment (CPE) approach to the global proteome analysis of human mammary epithelial cells (HMECs) which significantly improved both sequence coverage of protein identifications and the overall proteome coverage. The cysteinyl peptides were specifically enriched by using a thiol-specific covalent resin, fractionated by strong cation exchange chromatography, and subsequently analyzed by reversed-phase capillary LC-MS/MS. An HMEC tryptic digest without CPE was also fractionated and analyzed under the same conditions for comparison. The combined analyses of HMEC tryptic digests with and without CPE resulted in a total of 14 416 confidently identified peptides covering 4294 different proteins with an estimated 10% gene coverage of the human genome. By using the high efficiency CPE, an additional 1096 relatively low abundance proteins were identified, resulting in 34.3% increase in proteome coverage; 1390 proteins were observed with increased sequence coverage. Comparative protein distribution analyses revealed that the CPE method is not biased with regard to protein M(r) , pI, cellular location, or biological functions. These results demonstrate that the use of the CPE approach provides improved efficiency in comprehensive proteome-wide analyses of highly complex mammalian biological systems.