Biotic interactions in microbial communities as modulators of biogeochemical processes : methanotrophy as a model system

Microbial interaction is an integral component of microbial ecology studies, yet the role, extent, and relevance of microbial interaction in community functioning remains unclear, particularly in the context of global biogeochemical cycles. While many studies have shed light on the physico-chemical cues affecting specific processes, (micro)biotic controls and interactions potentially steering microbial communities leading to altered functioning are less known. Yet, recent accumulating evidence suggests that the concerted actions of a community can be significantly different from the combined effects of individual microorganisms, giving rise to emergent properties. Here, we exemplify the importance of microbial interaction for ecosystem processes by analysis of a reasonably well-understood microbial guild, namely, aerobic methane-oxidizing bacteria (MOB). We reviewed the literature which provided compelling evidence for the relevance of microbial interaction in modulating methane oxidation. Support for microbial associations within methane-fed communities is sought by a re-analysis of literature data derived from stable isotope probing studies of various complex environmental settings. Putative positive interactions between active MOB and other microbes were assessed by a correlation network-based analysis with datasets covering diverse environments where closely interacting members of a consortium can potentially alter the methane oxidation activity. Although, methanotrophy is used as a model system, the fundamentals of our postulations may be applicable to other microbial guilds mediating other biogeochemical processes

Wind environment evaluation on major town of Malaysia

This study focus on wind flow or wind environment of residential areas in Peninsular Malaysia, Sabah and Sarawak. Natural wind flow is one of the most effective methods to help achieve the energy saving in large cities especially under the tropical climate like Malaysia. The weather in Malaysia is characterized by four monsoon regimes, namely, the southwest monsoon, northeast monsoon and two shorter periods of inter-monsoon seasons. For this study, the data of wind velocity in twentytwo (22) weather station in Malaysia obtained from Meteorological Department and considered in wind environment evaluations. Then that data of wind velocities will convert to 1.5 in height at all measuring points were calculated by using the law. The result compared by Table 2.2 in previous researches (Kubota and Miura et al., 2002). From the study, it was found out, in Malaysia there are only two type of wind. First type is weak wind means that area are discomfort thermal and the second type is comfort range to strong wind means that area are comfort thermal. The minimum value of mean wind speed from 2005 to 2009 is O.mis in mean temperature is over 2C at Sitiawan. For the maximum value of mean wind speed is I .7m/s in average value of mean temperature is 276C at Mersing. Base on results, it can be concluded that when considering wind flow at a residential area, terrace housing is not a suitable option for towns located on the south of the Peninsular. It was prefer for high-rise building because it was considered this location of towns was weak wind condition. On the other hand, the major towns exclude the south of the Peninsular including Sabah and Sarawak, they was under the comfort thermal. So, terrace housing or high-rise building is suitable option

Neighbor-joining tree based on 147 deduced amino acid positions from 949 <i>mcrA</i> sequences.

<p>Phylogenetic nodes verified by a maximum likelihood tree are marked with closed circles. The outer branches of distinct clusters are collapsed, and those containing OTUs defined in this study are marked in blue. Only representative sequences for the OTUs have been incorporated into the tree and are depicted as ‘OTU name (accession number, number of sequences representing the OTU)’. Environmental clusters were labeled with two reference sequences showing maximum phylogenetic distance within the respective cluster, given as ‘name 1 (accession number 1), name 2 (accession number 2). The corresponding tRFs were calculated <i>in silico</i> using the TRiFLe package <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0053656#pone.0053656-Junier1" target="_blank">[64]</a> and are given to the right. Scale bar: 0.09 changes per amino acid position. The outgroup is <i>Methanopyrus kandleri</i>.</p

Multivariate analysis of relative abundances of terminal restriction fragments (tRF).

<p>(<b>A</b>) Biplot of a constrained correspondence analysis (CCA). Two constraints were applied: CH₃F concentration and the type of nucleic acid, <i>i.e.</i> DNA or mRNA. The CCA explains about 71% of overall variation, with CCA1 being the most important axis. The arrows indicate the direction in which constraints correlate with the ordination axes. Confidence ellipses (95%) surround the centers of DNA- and mRNA-derived communities, respectively. Closed circles represent the samples, and black triangles the different tRFs. The triangle surrounded by a red outline corresponds to tRF 133, the numerically dominant fragment. (<b>B</b>) Multivariate regression tree (MRT) based on squared Euclidean distances. The vertical spacing of the branches is proportional to the error in the fit; the first split reduces the error by 75%. The tree is pruned, i.e. the least important splits have been removed. Barplots at the leaves show the relative abundance of different tRFs; from left: 126, 133, 503, 648, 652, 663, 683, 743, and 752 bp. As in panel A, tRF 133 is marked by a red outline.</p

Experiments quantifying methane oxidation from the difference between methane fluxes measured with and without CH₃F.

<p>Experiments quantifying methane oxidation from the difference between methane fluxes measured with and without CH₃F.</p

Accumulation of acetate and methane (A), and the respective δ¹³C signatures in ‰ VPDB (B) depending on initial concentrations of methyl fluoride; δ¹³C_acetate is the combined signature for both C-atoms.

<p>Data are endpoint measurements and not corrected for initial concentrations. The fitted dose-response curves follow a log-logistic model with the parameters ED₅₀ (effective dose for 50% inhibition), upper limit, and slope, while the lower limit was fixed to the respective averages for 0% CH₃F. ED₅₀, ED₉₀, and ED₉₅ are marked by red lines. (<b>C</b>) Box-plot summarizing accumulation of methane and acetate in control (n = 3) and in samples with CH₃F≥0.75%, n = 6) after 14 days of anoxic incubation.</p

Residuals, the difference between real and estimated size, of a FAM-labeled size standard used as ‘sample’ in t-RFLP analysis.

<p>Data from three replicate runs are shown. Fit: fifth order polynomial, red line; 95% prediction intervals: black lines.</p

Ammonia-limited conditions cause of Thaumarchaeal dominance in volcanic grassland soil

The first step of nitrification is carried out by ammonia-oxidizing bacteria (AOB) and archaea (AOA). It is largely unknown, by which mechanisms these microbes are capable of coexistence and how their respective contribution to ammonia oxidation may differ with varying soil characteristics. To determine how different levels of ammonium availability influence the extent of archaeal and bacterial contributions to ammonia oxidation, microcosm incubations with controlled ammonium levels were conducted. Net nitrification was monitored and ammonia oxidizer communities were quantified. Additionally, the nitrification inhibitor allylthiourea (ATU) was applied to discriminate between archaeal and bacterial contributions to soil ammonia oxidation. Thaumarchaeota, which were the only ammonia oxidizers detectable at the start of the incubation, grew in all microcosms, but AOB later became detectable and grew as well. Low and high additions of ammonium increasingly stimulated AOB growth, while AOA were only stimulated by the low addition. Treatment with ATU had no effect on net nitrification and sizes of ammonia-oxidizing communities suggesting that the effective concentration of ATU to discriminate between archaeal and bacterial ammonia oxidation is not the same in different soils. Our results support the niche differentiating potential of ammonium concentration for AOA and AOB and we conclude that ammonium limitation can be a major reason for absence of detectable AOB in soil.Keywordsammonia-oxidizing archaeaammonia-oxidizing bacterianitrificationallylthioureaammonium© FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions{at}oup.co

Abundances of the 22 operational taxonomic units (OUTs) with a maximum intra-group distance of 5% (AA) in the clone library.

<p>Clones were derived from samples taken before (‘start’, based on DNA) and after (‘control’ and 3.85% CH₃F, based on transcripts) anoxic incubation for 14 days. OTU number and affiliation to families are given as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0053656#pone-0053656-g004" target="_blank">Figure 4</a>. Msarc: <i>Methanosarcinaceae</i>, Mcell: <i>Methanocellales</i>, Mbac: <i>Methanobacteriales</i>, Msaeta = <i>Methanosaetaceae</i>, Fen = Fen cluster, Msarc-like = uncertain affiliation, but nearest to <i>Methanosarcinaceae</i>; NN = unknown cluster. Simulated p-values are from a Monte-Carlo simulation with 9999 replicates.</p

Soil warming and fertilization altered rates of nitrogen transformation processes and selected for adapted ammonia-oxidizing archaea in sub-arctic grassland soil

The balance of microbial nitrogen (N) transformation processes in sub-arctic terrestrial ecosystems is most likely affected by global change, with potential feedbacks to greenhouse gas emissions and eutrophication. Soil temperature and N availability – their global increases being two of the most pressing global change features - will be prime drivers of N dynamics and microbial community structure, but little is known about their interactive effects in these ecosystems. We utilized geothermally warmed soils from Iceland as a natural experiment for assessing fertilization and warming effects on gross soil N transformation processes. Experimental incubations of these soils at different temperatures coupled with a dual 15N-labelling/-tracing approach and pyrotag transcript-sequencing allowed for the analysis of independent and combined impacts of N fertilization and temperature shifts on gross N mineralisation, nitrification, and ammonium and nitrate immobilisation rates and archaeal ammonia-oxidizing (AOA) communities, being the key ammonia oxidizers in this soil. Gross nitrification in warmed soil was increased in relation to ambient temperature soil and exhibited a higher temperature optimum. Concomitantly, our results revealed a selection of AOA populations adapted to in situ soil temperatures. Phylogenetically distinct populations of actively ammonia-oxidizing archaea exhibited conserved temperature optima. N mineralization and nitrification showed higher sensitivities in response to short-term temperature changes if the soils had been warmed. In part, the influence of short-term temperature changes could however be neutralized by the effects of N fertilization. Long-term N fertilization alone affected only gross N mineralization. However, all gross N transformation rates were significantly altered by the interactive effects of N fertilization and soil warming. We conclude that in order to reliably predict effects of global change on sub-arctic soil N transformation processes we need to consider multiple interactions among global change factors and to take into account the capacity of soil microbial populations to adapt to global change conditions