Community transcriptomics reveals unexpected high microbial diversity in acidophilic biofilm communities

Abstract

A fundamental question in microbial ecology relates to community structure, and how this varies across environment types. It is widely believed that some environments, such as those at very low pH, host simple communities based on the low number of taxa, possibly due to the extreme environmental conditions. However, most analyses of species richness have relied on methods that provide relatively low ribosomal RNA (rRNA) sampling depth. Here we used community transcriptomics to analyze the microbial diversity of natural acid mine drainage biofilms from the Richmond Mine at Iron Mountain, California. Our analyses target deep pools of rRNA gene transcripts recovered from both natural and laboratory-grown biofilms across varying developmental stages. In all, 91.8% of the B254 million Illumina reads mapped to rRNA genes represented in the SILVA database. Up to 159 different taxa, including Bacteria, Archaea and Eukaryotes, were identified. Diversity measures, ordination and hierarchical clustering separate environmental from laboratory-grown biofilms. In part, this is due to the much larger number of rare members in the environmental biofilms. Although Leptospirillum bacteria generally dominate biofilms, we detect a wide variety of other Nitrospira organisms present at very low abundance. Bacteria from the Chloroflexi phylum were also detected. The results indicate that the primary characteristic that has enabled prior extensive cultivation-independent 'omic' analyses is not simplicity but rather the high dominance by a few taxa. We conclude that a much larger variety of organisms than previously thought have adapted to this extreme environment, although only few are selected for at any one time.

Schrödinger’s microbes: Tools for distinguishing the living from the dead in microbial ecosystems

“…RNA-based methods (Table 1 ) have been used in a variety of environments, across a broad spectrum of microorganisms, and via a number of techniques, including microarrays, qPCR, 16S ribosomal RNA (rRNA) sequencing, and (meta)transcriptomics, each typically requiring an initial reverse transcription step (summarized in Fig. 5 ) [ 95 – 102 ]. Each of these approaches can potentially reveal the identity of viable microorganisms.…”

“…Each of these approaches can potentially reveal the identity of viable microorganisms. As messenger ribonucleic acid (mRNA) is extremely short-lived (with an average half-life of minutes in active cells and even less as a free molecule in the environment [ 103 , 104 ]), approaches focused on mRNA can track specific microbial metabolic responses on short timescales [ 95 , 102 , 105 ]. Compared to mRNA, rRNA has a half-life of days [ 106 ] and is more abundant in cells (approximately 18% of the dry weight of a bacterial cell [ 107 ] and up to 90% of total cellular RNA is rRNA [ 108 ]).…”

Microbial diversity and metabolic networks in acid mine drainage habitats

“…(“group IV”) has recently been detected via metagenomic data as a minority member in archaea-dominated low-pH biofilms in the Richmond mine (Goltsman et al, 2013 ). Other Nitrospirae -related groups have been recently obtained from the transcriptome of natural acid mine drainage biofilms collected at the Richmond mine, which include sequences related to the Magnetobacterium genus, as well as other uncultured and unclassified Nitrospiraceae (Aliaga Goltsman et al, 2014 ).…”

A decade of metaproteomics: Where we stand and what the future holds

“…Acid mine drainage biofilm 159 [25] 477 000 4259 [22] Specific cytochromes involved in iron oxidation [2,15]. Activated sludge 1000 [73] 3 000 000 5000 [69] Proteins constituting exopolymeric substances [12][13][14] Ocean water 160 [74] 480 000 5600 [28] Proteorhodopsins [30,31] Surface waters differ substantially with regards to nutrients, light, and microbial activities.…”