Palmer et al. 2010

Palmer K, Drake HL, Horn MA. 2010. Association of novel and highly diverse acid-tolerant denitrifiers with N2O fluxes of an acidic fen. Applied and Enironmental Microbiology 76: 1125-1134.

These authors examined soils from an acidic fen in southern Germany, and discovered novel denitrifiers that are apparently adapted to local conditions and contribute to the cycling of nitrogen within the fen. Methods employed included measurement of soil parameters, microcosms to examine denitrification rates (both total denitrification and net production / consumption of N2O), cell counts of cultured organisms, and phylogenetic analysis using narG and nosZ sequences and RFLP.

Palmer et al. 2009

Palmer K, Drake HL, Horn MA. 2009. Genome-derived criteria for assigning environmental narG and nosZ sequences to operational taxonomic units of nitrate reducers. Applied and Environmental Microbiology 75: 5170-5174.

These authors compared the sequences of narG and nosZ genes to corresponding sequences of 16s rRNA genes, using in-silico analysis of sequences downloaded from GenBank. While similarities above 97% are commonly used for species- or genus-level taxonomic delineation for 16s sequences, this analysis found much lower threshold similarities for such delineation using the structural genes.

This paper is confusing to me. One part of the text appears to contradict itself, when the authors state that the Nar operon in Pseudomonas stutzeri A1501 is putatively alien in origin (i.e. recent horizontal transfer), then go on to state in the same paragraph that it appears unlikely that the Nar operon was horizontally transferred in any species. I may just be misunderstanding the meaning of the term “putatively alien” in regards to a bacterial gene sequence.

A greater puzzle is presented by the list of nosZ sequences. These authors downloaded 85 such sequences, where my own attempts to extract data from GenBank resulted in only 42 unique nosZ sequences. The list in a supplementary table includes several cases of multiple accessions of the same species but of different PD. The paper these clusters of PD-sequences are derived from is Dandie et al. (2007); a quick scan of this paper did not reveal what the distinction “PD” indicates.

Schmidt et al. 2008

Schmidt SK, Reed SC, Nemergut DR, Grandy AS, Cleveland CC, Weintraub MN, Hill AW, Costellow EK, Meyer AF, Neff JC, Martin AM. 2008. The earliest stages of ecosystem succession in high-elevation (5000 metres above sea level), recently deglaciated soils. Proceedings of the Royal Society of London, Series B 275: 2793-2802.

These authors describe the microbial community and soil parameters of a chronosequence at the foreground of a receding glacier high in the Peruvian Andes. From a combination of aerial photography and previous work at this site, a series of sites of soils of increasing ages from zero to 79 years old was established. No surface plants, even lichens, are present on any of these new soils, and soil nutrient levels (carbon, nitrogen) are very low; the only organisms present are microorganisms.

Two previous hypotheses had been proposed to explain the dynamics of very early primary succession on new soil. Organic matter has been observed to accumulate slowly in new soils; the source of this material is either aeolian deposits (i.e. wind-borne plant detritus and pollen) or in-situ fixation of CO2 and N2. These are not mutually exclusive hypotheses, but the relative contributions of each are explored in this study.

The methods used here cover an extensive list of soil parameters. Three sets of soil samples were collected: for microbiological analysis, N-fixation measurement, and all other chemical analyses. The other chemical analyses include photosynthetic pigment extraction, soil total and mineral nitrogen, pyrolysis for identifying sources of carbon compounds (i.e. microbial-autotroph, microbial-heterotroph, plant), enzyme assays for common and informative microbial enzymes, and soil stability analysis of the resistance of these new soils to erosion forces such as water runoff.

These authors focused on the cyanobacterial fraction of the microbial community in this study; some details of other components of the biota are described in an earlier paper, Nemergut et al. (2007). Cyanobacteria are autotrophs also capable of fixing atmospheric nitrogen, thus they are ideal primary colonizers of new soil as they require little more than a source of moisture and air. Analysis of the community included the use of the P-test (Martin 2002); note that as in Nemergut et al. (2007), he is one of the authors of this study. The analytical approach is very similar to that employed in the earlier study, with a comparison of discovered sequences to published sequences from around the world. In this study, cyanobacterial sequences from zero and 4-year-old soils were similar to sequences from an extremely broad sample of habitats, including Antarctic lake ice, marine subseafloor sediments, urban aerosols, forest soils, and oil-polluted soils.

The soil chronosequence showed a clear pattern of stages of primary succession at every level of analysis. The soil microbial community became both more abundant and more diverse through time, soil nutrients increased, the chemical environment included increasing amounts and diversity of complex organic molecules, key enzyme pathways became established, and soil stability increased as soils aged. N-fixation showed a peak, with increasing N-fixation activity from the zero to 4-year-old soils (by two orders of magnitude), then declining by about half in the 79-year-old soils. This mirrors and precedes a widely-observed pattern in plant primary succession, in which nitrogen-fixing plants are among the first colonizers, but decline in abundance at later stages of succession. Enzyme and organic molecule patterns were consistent with a total absence of heterotrophs in the extremely young soils, increasing occurrence of organisms capable of decomposing plant matter in the 4-year-old soils, and a molecular ecology qualitatively similar to a mature plant-associated soil in the 79-year-old soil.

The list of procedures and level of detail of analysis in this paper is impressive. Many, though certainly not all, of these techniques will be models for my own work, especially in the summer of 2010. The molecular-diversity techniques pioneered by Martin (Martin 2002, Nemergut et al. 2007, this paper) as well as the techniques of analyzing soil pigments and soil nutrients are all very interesting.

Sørensen et al. 2006

Sørensen LI, Holmstrup M, Maraldo K, Christensen S, Christensen B. 2006. Soil fauna communities and microbial respiration in high Arctic tundra soils at Zackenberg, Northeast Greenland. Polar Biology 29: 189-195.

These authors sampled soil animals from three sites at Zackenberg station, Greenland, over three days in mid-summer. Two of the sites were considered mesic heath, with a mix of Cassiope tetragona and other High Arctic species of plants, while the third site was dominated by Dryas spp. and was considered dry heath; snow melts from the dry heath up to 20 days earlier than from the mesic heaths. Soil samples ranging down to about 6cm depth were collected, stored at 5ºC for up to two weeks, and analyzed by a range of methods in the laboratories in Europe.

Different groups of soil animals were extracted by varying methods. Soil microarthropods, a diverse group dominated by Collebola and Acari, were extracted by modified MacFadyen funnels into Benzoic acid. Enchytraeids and dipteran larvae were extracted in Baermann wet funnels with heating of the samples, into tap water. Protozoa were washed from soils in water and grown on media plates in the dark at 10ºC. Nematodes were collected by the Blender-Cotton wool method of Schouten and Arp (1991). Soil microbial respiration was measured in serum bottles, with the CO2 concentration in the headspace measured at zero, 5 and 25 hours, with a fully factorial design of nutrient amendments of C, N, and P. Soil pH and soil organic matter content, but not moisture content or other nutrient concentrations were determined using methods not clearly described, though presumably these procedures were similar to standard methods.

Once abundance and biomass data was collected, comparisons between plots were made using multivariate analysis and a software package named PRIMER 5.0. My understanding is the species counts were (log+1) transformed to reduce the influence of very abundant species, then analyzed using an approach similar to Principal Components Analysis. The result of this analysis was a clear difference between the dry heath and the two mesic heaths, while the two mesic heaths were not different from each other in parameter-space. A Bray-Curtis similarity matrix was also involved, though I’m not certain I understand how.

Different taxonomic groups were identified to different taxonomic levels; 19 species of Collembola and 7 species of Enchytraeids were found, for example, but Acari were identified to suborder (Cryptostigmata (oribatids), Prostigmata, Mesostigmata) and nematodes and protozoans were counted at those high taxonomic levels. While the two mesic heath sites were only marginally significantly different from each other, there was a clear increase in abundances in the dry heath site. For collembola at least, the dry heath site was also dominated by two highly abundant species, which differed from the majority of species in the mesic sites by being unpigmented and associated with sub-surface, rather than soil-surface, regions in the soil. The higher abundance of probably bacteria-eating nematodes at the dry heath strongly suggests higher turnover of microorganisms as well as generally higher biological activity from the higher populations of most soil animals.

These authors suggest higher organic matter decomposition rates at the dry heath, which seems reasonable given the higher animal populations there. However, their attribution of higher soil pH there to higher respiration levels seems like more of a stretch, absent supporting mineralogical and soil-nutrient data.

This paper provides an excellent example of the data that can be collected and analyzed from a brief but intensive study of soil invertebrates at a High Arctic site. In addition, meaningful information about differences in biodiversity between locations can be derived from studies of organisms not identified to fine taxonomic levels.

Li et al. 2009

Li X-R, Du B, Fu H-X, Wang R-F, Shi J-H, Wang Y, Jetten MSM, Quan ZX. 2009. The bacterial diversity in an anaerobic ammonium-oxidizing (anammox) reactor community. Systematic and Applied Microbiology 32: 278-289.

These authors studied the bacterial community that developed inside a bioreactor running on sewage sludge under anaerobic conditions. Like Lim et al. (2008), the main focus of this study was in the applications of ammonia-oxidizing bacteria (AOB) to water treatment facilities. The expected chemistry of anaerobic ammonia oxidation catalyzed by microorganisms (“anammox”) includes the use of nitrite as the electron acceptor in a near-one-to-one ratio with the consumption of ammonia or ammonium. The energy derived from this process is used by the cell to fix CO2, thus making these organisms autotrophs. This alters the underlying stoichiometry slightly, as some nitrite is diverted to CO2 fixation rather than ammonia oxidation.

The study of anaerobic AOB is still quite new, with the five described genera of such organisms all named with “Candidatus” prefixes, indicating recent species descriptions. All are in one group (taxonomic level unknown), the Brocadiales, within the phylum Planctomycetes. Aerobic AOB are in other groups, and include some species within the genus Nitrosomonas in the Beta-Proteobacteria that are capable of limited ammonia-oxidizing activity under anaerobic conditions, and can apparently survive long periods without oxygen.

These authors did not develop novel primers for PCR or qPCR in this study. Instead, they used published primer sets; I gather they did not use the TaqMan double-dye system for qPCR, as no mention of probes is made. The target genomic sequences were portions of the 16s rRNA gene, using E. coli as a standard. Oddly, the overall procedure included normal PCR, followed by cloning and insertion into plasmids, followed by qPCR of plasmid DNA containing the 16s sequences. It is unclear to me exactly why this was done, though later in the paper there are a few sequence-based phylogenetic trees that might have been based on sequences derived from this cloning procedure. In any case, the qPCR did provide informative results regarding the composition of bacterial groups within the reactor.

Of the sequences identified, the great majority were unlike cultivated organisms, highlighting the utility of these techniques in studying environmental samples. AnAOB produced approximately 16% of sequences, with aerobic AOB less than 1%. Non-AOB in three phyla constituted the majority of sequences, including 38% Chlorobi, 21% Chloroflexi, and 7% Bacteriodetes. These are filamentous heterotrophic bacteria, and appear to be closely associated with the granules that formed in the reactor solution after a few months. These authors suggest further research on the ecophysiology of these groups to answer questions regarding energy and material cycles within these systems.

In addition to 16s sequences, the hzo locus was also studied. This is a gene that produces an enzyme that catalyzes the oxidation of hydrazine (rocket fuel; N2H4) to N2 gas. No mention is made of the possibilities for N2O production or consumption in this process. The gene is restricted to AnAOB only, or at least that is the inference based on the observation that hydrazine is a unique intermediate molecule of the anammox process.

This study provides a useful example of the combination of qPCR and molecular-phylogenetic approaches in studying a microbiological system. Applied together, the two approaches allow the extraction of useful information regarding taxonomic diversity, both richness and evenness, among functional groups of organisms.

Michalyna 1971

Michalyna W. 1971. Distribution of various forms of aluminum, iron and manganese in the orthic gray wooded, gleyed orthic gray wooded and related gleysolic soils in Manitoba. Canadian Journal of Soil Science 51: 23-36.

This author examined soil Al, Fe, and Mn in some poorly drained soils of the Gleysolic order in western Manitoba, looking for indicators for soil classification that would cover some of the deficiencies of the previous criteria. The distribution of these metals, including the ratio of oxalate-extractable to dithionite-extractable iron representing amorphous and total Fe(III)-oxide forms, respectively, was a useful criterion for classification.

Iron of all types was concentrated in the upper horizons of these soils, with the highest levels in the BA and B horizons. The ratio of amorphous to total Fe(III) was also highest in these horizons, and declined with depth. This suggests amorphous Fe(III) is most abundant in relatively oxidizing conditions in these wet soils. Water content is not reported, except to note that some soils are “imperfectly drained”, others are “poorly drained”.

The ratio of amorphous to total Fe(III) found in these soils ranged from about 0.1 to about 1.2, with most measurements between 0.4 and 0.8. My own measurements, converted to the same ratio, range between 0.14 and 0.83.

Bohannan and Hughes 2003

Bohannan BJM, Hughes J. 2003. New approaches to analyzing microbial biodiversity data. Current Opinion in Microbiology. 6: 282-287.

These authors review the use of three broad approaches to studying microbial biodiversity in environments. The three are 1) parametric, 2) nonparametric, and 3) community phylogenetics. Each has advantages and disadvantages, and these authors suggest a combined approach may be most beneficial. Both 1) and 2) are based on Operational Taxonomic Units, to avoid the many problems of bacterial species identification, while 3) is based on molecular phylogenies, typically 16s rDNA.

Parametric approaches make simplifying assumptions and are based on some model of species richness in microbial communities; often this model is log-normal, in which some taxa are rare, some are abundant, and most are intermediate. These approaches extrapolate from patterns in a sample to the total environment. The obvious downside to parametric approaches is the vulnerability of the model to incorrect and difficult to test assumptions.

Nonparametric approaches avoid assuming any model, and instead are typically built on an approach analogous to mark-release-recapture. Sequences encountered more than once in a sample are recaptures, and the frequency of these doubletons is assumed to be related to how many unique sequences are present: more doubletons means fewer total sequences. As a downside, these approaches provide only a lower limit to actual richness, thus generally underestimating total diversity.

Community phylogenetics approaches avoid the OTU concept and thereby preserve useful data in the form of genetic information about sequences and sequence relationships. The downside of community phylogenetics approaches is they sample a clone library derived from the environment, not the environment directly, and can therefore not extrapolate from the sample to the environment.
This paper provides several useful examples of each approach, and supports the utility of Martin’s (2002) combined approach, which is what I would like to apply to my data to be collected in 2010. Figure 3 in this paper, for example, provides a useful overview of what Martin (2002) did, and how to make inferences about observed patterns.

Martin 2002

Martin AP. 2002. Phylogenetic approaches for describing and comparing the diversity of microbial communities. Applied and Environmental Microbiology 68: 3673-3682.

This author presents a synthesis of a set of statistical techniques for detailed analysis of biodiversity in the context of microbial communities. One new test, the P-test (for phylogenetics) is combined with the FST test to generate inferences about the quantified levels of difference in community composition when examining multiple microbial communities.

A review of existing methods for quantifying diversity is provided first, rapidly pointing out the not-unlikely circumstances under which inter-community differences would be either under- or over-estimated in the absence of explicit phylogenetic inference. Other types of phylogenetic inference in this context are examined, but one main problem with techniques such as the Shannon-Wiener index is its dependency on accurate information about frequency of taxa. The P-test, novel to this paper as far as I can tell, avoids this pitfall, and instead is based on an examination of the covariance between a phylogeny and the distribution of taxa in communities.Figure 3 from Martin (2002). The basis of the P test is the covariance between which community a sequence was found in, and the positions of sequences on the phylogenetic tree.

The P test is combined with the FST test to examine the partitioning of sequence variation between communities. A P test on its own is not particularly informative, because it says little about how variation is partitioned between communities vs. the total pool.The 2x2 grid of comparison of P test and FST test results, from Figure 4 of Martin (2002). Each possible outcome of significance for the two tests allows inference about the evolutionary and ecological history of a particular situation of microbial communities.

The raw data for the P test is sequence data, typically 16S rDNA. This author advocates whole-gene sequences for comparison, to provide the maximum data and maximum compatibility between different studies, but acknowledges the trade-off between sequence length and number of sequences that can be produced. These are also the raw data for FST, but how those raw data are treated before going into each test varies.

Under the P test, the sequence data are used to construct a phylogeny, incorporating all sequence data from all communities. This phylogeny is set to equal total branch lengths from the root to the tips (the tips being the currently-measured sequences), and a null model of branching through time (lineage-per-time) is built. Then the community occurrence of each sequence is mapped onto the phylogeny, and the covariance calculated.

The FST test takes in Theta values as its meat of calculation. Theta is the total genetic variation in a sample, and in FST the grand total theta for all communities combined is compared to the average within-community theta for all communities under consideration.

This combined approach is intended to be complimentary to existing methods of examining microbial diversity, such as methods for estimating species richness, and methods for examining microbial phylogenies. I think the author’s own words at the beginning of the discussion section provide a good summary:

“In this study I used standard quantitative methods of analysis borrowed from population genetics and systematics for describing and comparing microbial communities. Information gained from analysis of DNA sequences provided the basis for statistical analysis of communities in ways that advance inferences about the processes that may govern the compositions and functions of microbial communities. Furthermore, the analytical approaches advocated here make it possible to accomplish broad comparisons of ecological communities. For instance, a comparison of lineage-per-time plots across a diverse set of ecosystems might reveal differences in the phylogenetic compositions of ecological communities that would be invisible with standard ecological statistics that ignore the magnitude of genetic differences among sampled sequences.”

I think I would like to use this approach in the analysis of microbial communities I will conduct based on soil samples from the polar desert. This method seems at this point like a useful way to quantify diversity across the gradient of latitude I will be covering.

Floyd et al. 2002

Floyd R, Abebe E, Papert A, Blaxter M. 2002. Molecular barcodes for soil nematode identification. Molecular Ecology 11: 839-50.

These authors present a detailed description of and theory behind the MOTU concept. This analysis technique uses molecular sequence data to identify taxonomic units, hence the name Molecular Operational Taxonomic Unit. This paper uses the MOTU concept to examine and draw inferences about a collection of nematodes from a Scottish farm, finding high levels of species richness, and demonstrating a set of methods for rapid, inexpensive phylogenetics of a taxonomically-difficult group of animals.

Rogers 2001

Rogers DC. 2001. Revision of the nearctic Lepidurus (Notostraca). Journal of Crustacean Biology 21: 991-1006.

This author revised the tadpole shrimp (Crustacea: Branchiopoda: Notostraca) occurring in North America, with particular attention to the Western USA, and the description of a new species from northern California identified with the aid of DNA sequence data. The genus had previously been rather confused, with species descriptions and type locality often unclear or poorly described. Many of the morphological traits used in species identification in this group of crustaceans are known to be highly polymorphic within populations, and some are known to be frequently damaged or destroyed by predators or other factors, with subsequent regeneration if the animal survives.

In addition to describing the new species and providing a list of diagnostic traits for each of the six North American species, this author constructed a dichotomous tree for species identification, and tested the morphological effects of variation in diet and amputation / regeneration, removing some hypervariable traits from the diagnostic criteria. Biogeographic distributions focus on California and adjacent areas, with only a few collections from Canada.

Dillon 1984

Dillon RT. 1984. Geographic distance, environmental difference, and divergence between isolated populations. Systematic Zoology 33: 69-82.

This author examines the relative contributions to population divergence of selection and gene flow (or the lack thereof) using 25 populations of freshwater snails occurring in extremely stable drainages in the south-eastern USA. The system used here has clear advantages for a study that attempts to disentangle these frequently-confounded variables.

Divergence between populations can be correlated by distance in two non-mutually-exclusive ways. A reduction in gene flow that may be associated with longer dispersal distances means that novel mutations take increasingly long times to reach further populations. Environmental differences tend to be spatially autocorrelated such that distant populations are likely to have more different environments and selection will therefore be different. However, if divergence/distance and divergence/environmental difference can be separated, then gene flow and selection can be examined independently.

The drainages of the southern Appalachians appear to have been highly stable since the Cretaceous. The snail Goniobasis proxima appears to be incapable of dispersal overland, though very rare cases of transport by birds or mammals may be responsible for establishing some populations. It is restricted to smaller streams of intermediate flow rates, many of which are distributed on both sides of the southern Appalachians and on the Piedmont (low plateau of small foothills) east of the mountains. Most of the populations examined in this study are completely isolated from each other, such that snails would have to either pass through the marine environment or over the (often very short) land barriers between populations. Development is direct, with egg masses attached to solid substrates producing crawling juveniles. This author notes that at any time, the majority of individuals are crawling upstream against the current, which apparently allows populations to stay approximately in the same place despite the occasional individual that must lose its grip and be swept downstream.

The analysis of population divergence here included comparisons among eight 25 x 25 symmetric matrices, constructed using a comprehensive range of variables including morphological features (shell height, aperture width, etc.), allozyme alleles for seven loci, and 15 environmental variables (11 components of water chemistry, plus temperature, flow rate, stream gradient, and parasite infections by trematodes) and a further independent assessment of environmental similarity derived from an examination of the diatom species diversity in the diets of each population.

Varying levels of genetic divergence were found throughout the study system, but most differences were relatively high compared to similar studies of other organisms. Allozyme alleles fell primarily into two categories: either they were present in all four study drainages, or they occurred in only a single population or small group of neighbouring populations. This suggests that all alleles arose either during a period when rapid spread across drainages was possible, or during a later period when dispersal was more difficult. The geological evidence strongly indicates extreme drainage stability, indicating that something about either the environment and / or the dispersal capabilities of G. proxima was different, perhaps during the Tertiary, than today.

No cline in morphology or allozymes was observed, which may be the result of a lack of gene flow preventing the spread of beneficial alleles. In other words, while nearby populations (overland) may experience very similar environments, adaptations in one population cannot spread to the other.

This author summarizes with a statement that both selection and gene flow restriction seem to be equally important in promoting morphological divergence in isolated populations. However, time since divergence may be the more important diversifying factor, and may underlie both selection and gene flow in this system. Furthermore, measures of divergence using allozymes indicate that time since isolation or gene flow may be more important than selection in structuring differences between populations.

Dillon and Frankis 2004

Dillon RT, Frankis RC. 2004. High levels of mitochondrial DNA sequence divergence in isolated populations of freshwater snails of the genus Goniobasis Lea, 1862. American Malacological Bulletin 19: 69-77.

These authors examined sequence divergence within and between populations and species of “prosobranch” freshwater gastropods in the south-eastern USA. These species are relatively well studied, and previous work by other authors had suggested very high levels of mtDNA heterogeneity, between populations and between species.

Part of the justification for this work is as a way of calibrating a new measurement tool: DNA sequences may be useful for systematic assignment, but if levels of sequence divergence are to be used to distinguish species, first the levels of divergence between species well-established by other means (e.g. interspecific hybridization trials) must be determined. These snails had previously been well studied for traits associated with concepts of species such as pre- and post-mating isolation (e.g. Dillon 1986).

The other major reason for this paper was to test the hypothesis that freshwater snail populations may be so old, so large, and so isolated that intrapopulation mtDNA sequence divergence is likely to swamp interpopulation (and interspecies) mtDNA divergence. Under this hypothesis, within-population levels of divergence will overlap with between-population levels. Populations studied here are extremely isolated, with no freshwater connections between them; this area was not inundated nor was it ice-bound by the Pleistocene glaciations, suggesting that some populations may have been isolated for millions of years.

The levels of divergence found in COI and 16S mtDNA sequences were extremely high, especially among populations of one species, Goniobasis proxima. In one population, individual conspecific snails collected from adjacent rocks may have more divergent mtDNA than individual snails collected from populations separated by over 400km of (impassable) land. In that same highly heterogeneous-mtDNA population, morphology and seven nuclear markers (allozymes) were essentially homogeneous.

The authors end with a caution that systematic inference must be made with care when faced with high levels of intrapopulation divergences. This paper appears to provide an example situation in mtDNA phylogeography that does not show the “barcode gap”, i.e. a clear distinction between intra- and interpopulation divergences.