scholarly journals An improved method for utilizing high-throughput amplicon sequencing to determine the diets of insectivorous animals

Author(s):  
Michelle A Jusino ◽  
Mark T Banik ◽  
Jonathan M Palmer ◽  
Amy K Wray ◽  
Lei Xiao ◽  
...  

DNA analysis of predator feces using high-throughput amplicon sequencing (HTS) enhances our understanding of predator-prey interactions. However, conclusions drawn from this technique are constrained by biases that occur in multiple steps of the HTS workflow. To better characterize insectivorous animal diets, we used DNA from a diverse set of arthropods to assess PCR biases of commonly used and novel primer pairs for the mitochondrial gene, cytochrome oxidase C subunit 1 (CO1). We compared diversity recovered from HTS of bat guano samples using a commonly used primer pair “ZBJ” to results using the novel primer pair “ANML”. To parameterize our bioinformatics pipeline, we created an arthropod mock community consisting of single-copy (cloned) CO1 sequences. To examine biases associated with both PCR and HTS, mock community members were combined in equimolar amounts both pre- and post-PCR. We validated our system using guano from bats fed known diets and using composite samples of morphologically identified insects collected in pitfall traps. In PCR tests, the ANML primer pair amplified 58 of 59 arthropod taxa (98%) whereas ZBJ amplified 24 of 59 taxa (41%). Furthermore, in an HTS comparison of field-collected samples, the ANML primers detected nearly four-fold more arthropod taxa than the ZBJ primers. The additional arthropods detected include medically and economically relevant insect groups such as mosquitoes. Results revealed biases at both the PCR and sequencing levels, demonstrating the pitfalls associated with using HTS read numbers as proxies for abundance. The use of an arthropod mock community allowed for improved bioinformatics pipeline parameterization.

2017 ◽  
Author(s):  
Michelle A Jusino ◽  
Mark T Banik ◽  
Jonathan M Palmer ◽  
Amy K Wray ◽  
Lei Xiao ◽  
...  

DNA analysis of predator feces using high-throughput amplicon sequencing (HTS) enhances our understanding of predator-prey interactions. However, conclusions drawn from this technique are constrained by biases that occur in multiple steps of the HTS workflow. To better characterize insectivorous animal diets, we used DNA from a diverse set of arthropods to assess PCR biases of commonly used and novel primer pairs for the mitochondrial gene, cytochrome oxidase C subunit 1 (CO1). We compared diversity recovered from HTS of bat guano samples using a commonly used primer pair “ZBJ” to results using the novel primer pair “ANML”. To parameterize our bioinformatics pipeline, we created an arthropod mock community consisting of single-copy (cloned) CO1 sequences. To examine biases associated with both PCR and HTS, mock community members were combined in equimolar amounts both pre- and post-PCR. We validated our system using guano from bats fed known diets and using composite samples of morphologically identified insects collected in pitfall traps. In PCR tests, the ANML primer pair amplified 58 of 59 arthropod taxa (98%) whereas ZBJ amplified 24 of 59 taxa (41%). Furthermore, in an HTS comparison of field-collected samples, the ANML primers detected nearly four-fold more arthropod taxa than the ZBJ primers. The additional arthropods detected include medically and economically relevant insect groups such as mosquitoes. Results revealed biases at both the PCR and sequencing levels, demonstrating the pitfalls associated with using HTS read numbers as proxies for abundance. The use of an arthropod mock community allowed for improved bioinformatics pipeline parameterization.


2017 ◽  
Vol 83 (17) ◽  
Author(s):  
Francesca De Filippis ◽  
Manolo Laiola ◽  
Giuseppe Blaiotta ◽  
Danilo Ercolini

ABSTRACT Target-gene amplicon sequencing is the most exploited high-throughput sequencing application in microbial ecology. The targets are taxonomically relevant genes, with 16S rRNA being the gold standard for bacteria. As for fungi, the most commonly used target is the internal transcribed spacer (ITS). However, the uneven ITS length among species may promote preferential amplification and sequencing and incorrect estimation of their abundance. Therefore, the use of different targets is desirable. We evaluated the use of three different target amplicons for the characterization of fungal diversity. After an in silico primer evaluation, we compared three amplicons (the ITS1-ITS2 region [ITS1-2], 18S ribosomal small subunit RNA, and the D1/D2 domain of the 26S ribosomal large subunit RNA), using biological samples and a mock community of common fungal species. All three targets allowed for accurate identification of the species present. Nevertheless, high heterogeneity in ITS1-2 length was found, and this caused an overestimation of the abundance of species with a shorter ITS, while both 18S and 26S amplicons allowed for more reliable quantification. We demonstrated that ITS1-2 amplicon sequencing, although widely used, may lead to an incorrect evaluation of fungal communities, and efforts should be made to promote the use of different targets in sequencing-based microbial ecology studies. IMPORTANCE Amplicon-sequencing approaches for fungi may rely on different targets affecting the diversity and abundance of the fungal species. An increasing number of studies will address fungal diversity by high-throughput amplicon sequencing. The description of the communities must be accurate and reliable in order to draw useful insights and to address both ecological and biological questions. By analyzing a mock community and several biological samples, we demonstrate that using different amplicon targets may change the results of fungal microbiota analysis, and we highlight how a careful choice of the target is fundamental for a thorough description of the fungal communities.


2020 ◽  
Author(s):  
Christopher Quince ◽  
Sergey Nurk ◽  
Sebastien Raguideau ◽  
Robert James ◽  
Orkun S. Soyer ◽  
...  

AbstractWe introduce a novel bioinformatics pipeline, STrain Resolution ON assembly Graphs (STRONG), which identifies strains de novo, when multiple metagenome samples from the same community are available. STRONG performs coassembly, followed by binning into metagenome assembled genomes (MAGs), but uniquely it stores the coassembly graph prior to simplification of variants. This enables the subgraphs for individual single-copy core genes (SCGs) in each MAG to be extracted. It can then thread back reads from the samples to compute per sample coverages for the unitigs in these graphs. These graphs and their unitig coverages are then used in a Bayesian algorithm, BayesPaths, that determines the number of strains present, their sequences or haplotypes on the SCGs and their abundances in each of the samples.Our approach both avoids the ambiguities of read mapping and allows more of the information on co-occurrence of variants in reads to be utilised than if variants were treated independently, whilst at the same time exploiting the correlation of variants across samples that occurs when they are linked in the same strain. We compare STRONG to the current state of the art on synthetic communities and demonstrate that we can recover more strains, more accurately, and with a realistic estimate of uncertainty deriving from the variational Bayesian algorithm employed for the strain resolution. On a real anaerobic digestor time series we obtained strain-resolved SCGs for over 300 MAGs that for abundant community members match those observed from long Nanopore reads.


PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7608
Author(s):  
Adam Šťovíček ◽  
Smadar Cohen-Chalamish ◽  
Osnat Gillor

It is assumed that the sequencing of ribosomes better reflects the active microbial community than the sequencing of the ribosomal RNA encoding genes. Yet, many studies exploring microbial communities in various environments, ranging from the human gut to deep oceans, questioned the validity of this paradigm due to the discrepancies between the DNA and RNA based communities. Here, we focus on an often neglected key step in the analysis, the reverse transcription (RT) reaction. Previous studies showed that RT may introduce biases when expressed genes and ribosmal rRNA are quantified, yet its effect on microbial diversity and community composition was never tested. High throughput sequencing of ribosomal RNA is a valuable tool to understand microbial communities as it better describes the active population than DNA analysis. However, the necessary step of RT may introduce biases that have so far been poorly described. In this manuscript, we compare three RT enzymes, commonly used in soil microbiology, in two temperature modes to determine a potential source of bias due to non-standardized RT conditions. In our comparisons, we have observed up to six fold differences in bacterial class abundance. A temperature induced bias can be partially explained by G-C content of the affected bacterial groups, thus pointing toward a need for higher reaction temperatures. However, another source of bias was due to enzyme processivity differences. This bias is potentially hard to overcome and thus mitigating it might require the use of one enzyme for the sake of cross-study comparison.


2019 ◽  
Author(s):  
Adam Šťovíček ◽  
Smadar Cohen-Chalamish ◽  
Osnat Gillor

It is assumed that the sequencing of ribosomes better reflects the active microbial community than the sequencing of the ribosomal RNA encoding genes. Yet, many studies exploring microbial communities in various environments, ranging from the human gut to deep oceans, questioned the validity of this paradigm due to the discrepancies between the DNA and RNA based communities. Here we focus on an often neglected key step in the analysis, the reverse transcription (RT) reaction. Previous studies showed that RT may introduce biases when expressed genes and ribosmal rRNA are quantified, yet its effect on microbial diversity and community composition was never tested. High throughput sequencing of ribosomal RNA is a valuable tool to understand microbial communities as it better describes the active population than DNA analysis. However, the necessary step of RT may introduce biases that have so far been poorly described. In this manuscript, we compare three RT enzymes, commonly used in soil microbiology, in two temperature modes to determine a potential source of bias due to non-standardized RT conditions. In our comparisons, we have observed up to 6 fold differences in bacterial class abundance. A temperature induced bias can be partially explained by G-C content of the affected bacterial groups, thus pointing towards a need for higher reaction temperatures. However, another source of bias was due to enzyme processivity differences. This bias is potentially hard to overcome and thus mitigating it might require the use of one enzyme for the sake of cross-study comparison.


2019 ◽  
Author(s):  
Adam Šťovíček ◽  
Smadar Cohen-Chalamish ◽  
Osnat Gillor

It is assumed that the sequencing of ribosomes better reflects the active microbial community than the sequencing of the ribosomal RNA encoding genes. Yet, many studies exploring microbial communities in various environments, ranging from the human gut to deep oceans, questioned the validity of this paradigm due to the discrepancies between the DNA and RNA based communities. Here we focus on an often neglected key step in the analysis, the reverse transcription (RT) reaction. Previous studies showed that RT may introduce biases when expressed genes and ribosmal rRNA are quantified, yet its effect on microbial diversity and community composition was never tested. High throughput sequencing of ribosomal RNA is a valuable tool to understand microbial communities as it better describes the active population than DNA analysis. However, the necessary step of RT may introduce biases that have so far been poorly described. In this manuscript, we compare three RT enzymes, commonly used in soil microbiology, in two temperature modes to determine a potential source of bias due to non-standardized RT conditions. In our comparisons, we have observed up to 6 fold differences in bacterial class abundance. A temperature induced bias can be partially explained by G-C content of the affected bacterial groups, thus pointing towards a need for higher reaction temperatures. However, another source of bias was due to enzyme processivity differences. This bias is potentially hard to overcome and thus mitigating it might require the use of one enzyme for the sake of cross-study comparison.


2019 ◽  
Author(s):  
Adam Šťovíček ◽  
Smadar Cohen-Chalamish ◽  
Osnat Gillor

It is assumed that the sequencing of ribosomes better reflects the active microbial community than the sequencing of the ribosomal RNA encoding genes. Yet, many studies exploring microbial communities in various environments, ranging from the human gut to deep oceans, questioned the validity of this paradigm due to the discrepancies between the DNA and RNA based communities. Here we focus on an often neglected key step in the analysis, the reverse transcription (RT) reaction. Previous studies showed that RT may introduce biases when expressed genes and ribosomes are quantified, yet its effect on microbial diversity and community composition was never tested. High throughput sequencing of ribosomal RNA is a valuable tool to understand microbial communities as it better describes the active population than DNA analysis. However, the necessary step of RT may introduce biases that have so far been poorly described. In this manuscript, we compare three reverse transcription enzymes, commonly used in soil microbiology, in two temperature modes to determine a potential source of bias due to non-standardized reverse transcription conditions. In our comparisons, we have observed up to 6 fold differences in bacterial class abundance. A temperature induced bias can be partially explained by G-C content of the affected bacterial groups, thus pointing towards a need for higher reaction temperatures. However, another source of bias was due to enzyme processivity differences. This bias is potentially hard to overcome and thus mitigating it might require the use of one enzyme for the sake of cross-study comparison.


Fuels ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 241-252
Author(s):  
Dyah Asri Handayani Taroepratjeka ◽  
Tsuyoshi Imai ◽  
Prapaipid Chairattanamanokorn ◽  
Alissara Reungsang

Extreme halophiles offer the advantage to save on the costs of sterilization and water for biohydrogen production from lignocellulosic waste after the pretreatment process with their ability to withstand extreme salt concentrations. This study identifies the dominant hydrogen-producing genera and species among the acclimatized, extremely halotolerant microbial communities taken from two salt-damaged soil locations in Khon Kaen and one location from the salt evaporation pond in Samut Sakhon, Thailand. The microbial communities’ V3–V4 regions of 16srRNA were analyzed using high-throughput amplicon sequencing. A total of 345 operational taxonomic units were obtained and the high-throughput sequencing confirmed that Firmicutes was the dominant phyla of the three communities. Halanaerobium fermentans and Halanaerobacter lacunarum were the dominant hydrogen-producing species of the communities. Spatial proximity was not found to be a determining factor for similarities between these extremely halophilic microbial communities. Through the study of the microbial communities, strategies can be developed to increase biohydrogen molar yield.


Viruses ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 806
Author(s):  
Shambhu G. Aralaguppe ◽  
Anoop T. Ambikan ◽  
Manickam Ashokkumar ◽  
Milner M. Kumar ◽  
Luke Elizabeth Hanna ◽  
...  

The detection of drug resistance mutations (DRMs) in minor viral populations is of potential clinical importance. However, sophisticated computational infrastructure and competence for analysis of high-throughput sequencing (HTS) data lack at most diagnostic laboratories. Thus, we have proposed a new pipeline, MiDRMpol, to quantify DRM from the HIV-1 pol region. The gag-vpu region of 87 plasma samples from HIV-infected individuals from three cohorts was amplified and sequenced by Illumina HiSeq2500. The sequence reads were adapter-trimmed, followed by analysis using in-house scripts. Samples from Swedish and Ethiopian cohorts were also sequenced by Sanger sequencing. The pipeline was validated against the online tool PASeq (Polymorphism Analysis by Sequencing). Based on an error rate of <1%, a value of >1% was set as reliable to consider a minor variant. Both pipelines detected the mutations in the dominant viral populations, while discrepancies were observed in minor viral populations. In five HIV-1 subtype C samples, minor mutations were detected at the <5% level by MiDRMpol but not by PASeq. MiDRMpol is a computationally as well as labor efficient bioinformatics pipeline for the detection of DRM from HTS data. It identifies minor viral populations (<20%) of DRMs. Our method can be incorporated into large-scale surveillance of HIV-1 DRM.


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