Dataset Information

Indirect methods produce higher estimates of fine root production and turnover rates than direct methods.

ABSTRACT: The production and turnover of fine roots play substantial roles in the biogeochemical cycles of terrestrial ecosystems. However, the disparity among the estimates of both production and turnover, particularly due to technical limitations, has been debated for several decades. Here, we conducted a meta-analysis to compare published estimates of fine root production and turnover rates derived from different methods at the same sites and at the same sampling time. On average, the estimates of fine root production and turnover rates were 87% and 124% higher, respectively, by indirect methods than by direct methods. The substantially higher fine root production and turnover estimated by indirect methods, on which most global carbon models are based, indicate the necessity of re-assessing the global carbon model predictions for atmospheric carbon sequestration in soils as a result of the production and turnover of fine roots.

SUBMITTER: Yuan ZY

PROVIDER: S-EPMC3494664 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Indirect methods produce higher estimates of fine root production and turnover rates than direct methods.

Yuan Z Y ZY Chen Han Y H HY

PloS one 20121109 11

The production and turnover of fine roots play substantial roles in the biogeochemical cycles of terrestrial ecosystems. However, the disparity among the estimates of both production and turnover, particularly due to technical limitations, has been debated for several decades. Here, we conducted a meta-analysis to compare published estimates of fine root production and turnover rates derived from different methods at the same sites and at the same sampling time. On average, the estimates of fine ...[more]

PMID: 23166603

Similar Datasets

Project description:BackgroundSensitive, rapid, and accessible diagnostics continue to be critical to track the COVID-19 pandemic caused by the SARS-CoV-2 virus. RT-qPCR is the gold standard test, and comparison of methodologies and reagents, utilizing patient samples, is important to establish reliable diagnostic pipelines.MethodsHere, we assessed indirect methods that require RNA extraction with direct RT-qPCR on patient samples. Four different RNA extraction kits (Qiagen, Invitrogen, BGI and Norgen Biotek) were compared. For detection, we assessed two recently developed Taqman-based modules (BGI and Norgen Biotek), a SYBR green-based approach (NEB Luna Universal One-Step Kit) with published and newly-developed primers, and clinical results (Seegene STARMag RNA extraction system and Allplex 2019-nCoV RT-qPCR assay). We also tested and optimized direct, extraction-free detection using these RT-qPCR systems and performed a cost analysis of the different methods evaluated here.ResultsMost RNA isolation procedures performed similarly, and while all RT-qPCR modules effectively detected purified viral RNA, the BGI system provided overall superior performance (lower detection limit, lower Ct values and higher sensitivity), generating comparable results to original clinical diagnostic data, and identifying samples ranging from 65 copies to 2.1 × 105 copies of viral genome/μl. However, the BGI detection system is more expensive than other options tested here. With direct RT-qPCR, simply adding an RNase inhibitor greatly improved detection, without the need for any other treatments (e.g. lysis buffers or boiling). The best direct methods detected ~ 10 fold less virus than indirect methods, but this simplified approach reduced sample handling, as well as assay time and cost.ConclusionsWith extracted RNA, the BGI RT-qPCR detection system exhibited superior performance over the Norgen system, matching initial clinical diagnosis with the Seegene Allplex assay. The BGI system was also suitable for direct, extraction-free analysis, providing 78.4% sensitivity. The Norgen system, however, still accurately detected samples with a clinical Ct < 33 from extracted RNA, provided significant cost savings, and was superior to SYBR green assays that exhibited reduced specificity.

Project description:The difficulty involved in quantifying biogeochemically significant microbes in marine sediments limits our ability to assess interspecific interactions, population turnover times, and niches of uncultured taxa. We incubated surface sediments from Cape Lookout Bight, North Carolina, USA, anoxically at 21°C for 122 days. Sulfate decreased until day 68, after which methane increased, with hydrogen concentrations consistent with the predicted values of an electron donor exerting thermodynamic control. We measured turnover times using two relative quantification methods, quantitative PCR (qPCR) and the product of 16S gene read abundance and total cell abundance (FRAxC, which stands for "fraction of read abundance times cells"), to estimate the population turnover rates of uncultured clades. Most 16S rRNA reads were from deeply branching uncultured groups, and ?98% of 16S rRNA genes did not abruptly shift in relative abundance when sulfate reduction gave way to methanogenesis. Uncultured Methanomicrobiales and Methanosarcinales increased at the onset of methanogenesis with population turnover times estimated from qPCR at 9.7 ± 3.9 and 12.6 ± 4.1 days, respectively. These were consistent with FRAxC turnover times of 9.4 ± 5.8 and 9.2 ± 3.5 days, respectively. Uncultured Syntrophaceae, which are possibly fermentative syntrophs of methanogens, and uncultured Kazan-3A-21 archaea also increased at the onset of methanogenesis, with FRAxC turnover times of 14.7 ± 6.9 and 10.6 ± 3.6 days. Kazan-3A-21 may therefore either perform methanogenesis or form a fermentative syntrophy with methanogens. Three genera of sulfate-reducing bacteria, Desulfovibrio, Desulfobacter, and Desulfobacterium, increased in the first 19 days before declining rapidly during sulfate reduction. We conclude that population turnover times on the order of days can be measured robustly in organic-rich marine sediment, and the transition from sulfate-reducing to methanogenic conditions stimulates growth only in a few clades directly involved in methanogenesis, rather than in the whole microbial community.IMPORTANCE Many microbes cannot be isolated in pure culture to determine their preferential growth conditions and predict their response to changing environmental conditions. We created a microcosm of marine sediments that allowed us to simulate a diagenetic profile using a temporal analog for depth. This allowed for the observation of the microbial community population dynamics caused by the natural shift from sulfate reduction to methanogenesis. Our research provides evidence for the population dynamics of uncultured microbes as well as the application of a novel method of turnover rate analysis for individual taxa within a mixed incubation, FRAxC, which stands for "fraction of read abundance times cells," which was verified by quantitative PCR. This allows for the calculation of population turnover times for microbes in a natural setting and the identification of uncultured clades involved in geochemical processes.

Dataset Information

Indirect methods produce higher estimates of fine root production and turnover rates than direct methods.

Publications

Indirect methods produce higher estimates of fine root production and turnover rates than direct methods.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets