A Genetic Rement Becoming Active Again
PLoS One. 2020; xv(12): e0244482.
Tracing the active genetic diversity of Microcystis and Microcystis phage through a temporal survey of Taihu
Helena 50. Pound
Section of Microbiology, The University of Tennessee, Knoxville, Tennessee, U.s. of America
Steven Westward. Wilhelm
Department of Microbiology, The University of Tennessee, Knoxville, Tennessee, United States of America
Jean-François Humbert, Editor
Received 2020 Jul 31; Accepted 2020 Dec xi.
- Supplementary Materials
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S1 Fig: McyA cladogram. Cladogram of toxin-encoding candidate contigs (mcyA). Inner color ring indicates taxonomic group and outer heatmap rings bespeak the average expression of each candidate per month. Black dots indicate bootstrap values greater than 0.5 and cherry dots indicate no expression.
(TIF)
GUID: 4483E6C8-26DE-457B-B6B8-17C069942797
S2 Fig: Terminase cladogram. Cladogram of phage terminase candidate contigs. Inner colour ring indicates Microcystis phage group and outer heatmap rings indicate the boilerplate expression of each candidate per month. Black dots indicate bootstrap values greater than 0.v and red dots indicate no expression.
(TIF)
GUID: C858197B-CC96-4CE6-9AAB-7CEF2F751946
S3 Fig: NIES-88 genome. Genome scaffold map of NIES-88 (Accession number NZ_JXYX010000002). Orange open reading frames indicate phage-like genes.
(TIFF)
GUID: 3211890C-422B-4740-94DD-EDB38AFDB055
S1 Table: Environmental parameters. Table of ecology parameters measured with each sample collected and the associated biplot scores for the RpoB approved correspondence analysis.
(XLSX)
GUID: 958DAC98-1A6D-47A9-8EBC-F9E0BB6057F6
S2 Table: Genotype sequences. Sequences of RpoB, McyA, and terminase genotypes identified and analyzed.
(XLSX)
GUID: 70B015FC-9554-4D78-829F-8F9E44080392
- Information Availability Statement
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Sequences are available from the MG-RAST database ("Lake_Taihu_metatranscriptome_project").
Abstract
Harmful algal blooms are commonly thought to be dominated by a single genus, but they are not homogenous communities. Electric current approaches, both molecular and culture-based, oftentimes overlook fine-scale variations in community composition that can influence blossom dynamics. We combined homology-based searches (BLASTX) and phylogenetics to distinguish and quantify Microcystis host and phage members beyond a summer season during a 2014 Microcystis- dominated bloom that occurred in Lake Tai (Taihu), China. We plant 47 different genotypes of the Microcystis-specific DNA-dependent RNA polymerase (rpoB), which included several morphospecies. Microcystis flos-aquae and Microcystis wesenbergii deemed for ~86% of total Microcystis transcripts, while the more commonly studied Microcystis aeruginosa only accounted for ~7%. Microcystis genotypes were classified into three temporal groups according to their expression patterns across the course of the bloom: early, abiding and late. All Microcystis morphospecies were present in each group, indicating that expression patterns were likely dictated by competition driven past ecology factors, not phylogeny. We identified iii chief Microcystis-infecting phages based on the viral terminase, including a novel Siphoviridae phage that may be capable of lysogeny. Within our dataset, Myoviridae phages consequent with those infecting Microcystis in a lytic manner were positively correlated to the early host genotypes, while the Siphoviridae phages were positively correlated to the late host genotypes, when the Myoviridae phages limited putative genetic markers for lysogeny. The expression of genes in the microcystin-encoding mcy cassette was estimated using mcyA, which revealed 24 Microcystis-specific genotypes that were negatively correlated to the early host genotypes. Of all ecology factors measured, pH best described the temporal shift in the Microcystis community genotypic composition, promoting hypotheses regarding carbon concentration mechanisms and oxidative stress. Our work expounds on the complexity of HAB events, using a well-studied dataset to highlight the need for increased resolution of community dynamics.
Introduction
Bodies of h2o around the world are fated by annual blooms of algal biomass. Known as harmful algal blooms (HABs), these events of economic and environmental concerns are frequently associated with the production of toxic compounds and/or excessive biomass accumulation [i, two]. Nigh bloom events, be they summertime or winter / freshwater or marine, occur when a single genus of algae evades normal biological constraints and achieves numerical dominance in a customs [3]. As such, events are typically referred to past the name of the dominant genus: for case, in China's Lake Tai, (Taihu in Standard mandarin) these are generally referred to as Microcystis spp. blooms. The annual reoccurrence of similar species has been established in scientific literature, providing an splendid report system for genetic shifts in microbial communities [4].
Ecosystem processes are driven by the composition and function of the species present. Genotypic diversity of these species is of critical importance to community stability and performance [5]. This multifariousness tin can be catalogued in several ways, including by the richness and evenness of species or subspecies present and/or the number and composition of functional roles present [6, seven]. Genotypic diversity tin can arise in multiple ways, and is an ongoing process [eight]. At the aforementioned time selective pressures are constant for microorganisms. Thus genetic drift occurs based on the stochastic furnishings of random selection [9], niche division and resource utilization efficacy [x], environmental option, and biotic interactions with beau customs members including predation [11] and symbiosis [12]. Blended genotypic diversity in an ecosystem can influence the phenotypic community, which governs many ecosystem traits including biomass accumulation, the production of secondary compounds, and resiliency to abiotic and biotic stressors.
Genetic diversity may become particularly important during HAB events, given the presumed lack of community diversity associated blooms. Although blooms are typically dominated by only a few species, usually members of the same genus, information technology is critical to call back that these communities are non homogenous. Not only are there many different genotypes or strains of the ascendant taxa present, the spatial and temporal distribution of these genotypes can vary widely over the bloom duration. Indeed, there take been many observations of genotypic shifts in Microcystis spp. blooms, fifty-fifty over the course of a single bloom event [13–16], where the focus is often on the ability (or lack at that place-of) of these cyanobacteria to produce to potent hepatotoxin microcystin (aka "fast-death factor", [17]). Most studies accept used polymerase chain reaction (PCR) approaches to characterize diverse genotypes and their toxicity [18], which comes with the risk of some genotypes being excluded. As toxicity is not unique trait of a single species or strain, the community composition of co-occurring toxic organisms should be considered in toxin research [19].
The democratization in molecular biological tools has provided many new avenues of study in HABs. However, these avant-garde tools tin can often overlook the constant disconnect that is the dissimilarities between results from lab studies and measured environmental processes. While controlled laboratory experiments and genomic sequencing of cultured isolates provide of import information, they cannot represent the complexity of natural diversity and function present in an surroundings. For this reason, it may exist less desirable to quantify the expression of genes in an environmental sample by recruiting sequences to the genome of a cultured isolate. This practice results in an underestimation of true diversity and tin obscure species or strain level dynamics that may better reflect responses to environmental conditions.
Faced with the to a higher place, we sought to characterize the genotypic variety of a spatially big and temporally extended Microcystis spp.-dominated bloom using metatranscriptomic sequencing. While previous efforts have examined specific subpopulations through recruitment to a model lab strain [4], nutrient cycling genes [20] and viruses every bit drivers of mortality [21, 22], our efforts here were focused on the specific question of how diverse the flower forming community was. We used a homology-based BLASTX approach accompanied by phylogenetics to identify the species and strains of Microcystis that were present and to quantify how their distribution varied across the form of this bloom. The analyses revealed patterns in genotype-specific expression that were linked to abiotic and biotic environmental factors, including pH and viral infection, respectively. We were also able to link changes in genotypic-marker expression to changes in toxin gene activity. Our analyses provide evidence that diversity, equally well equally pocket-sized-calibration patterns, are much broader than previously idea inside the Microcystis community and present new hypotheses regarding the role of genotypic diversity in blossom dynamics.
Methods
Sampling and sequencing
Water samples were nerveless monthly from May to October from 9 stations in Northwestern Lake Taihu in 2014 during daylight hours, as previously described [4, twenty–22]. Based on anecdotal observations (east.g., see Fig 1), we know that a Microcystis-dominated bloom had established biomass by the time our sample drove started in June, yet connected to accumulate through to October. Whole water samples were nerveless at the surface and passed through a 0.22-μm pore-size Sterivex™ filter, excess water removed, and the unit of measurement filled with RNAlater™ (Invitrogen) until extraction. Basic physical parameters were also measured at time of sampling using a multiparameter water quality sonde (YSI 6600 V2) and include dissolved oxygen, water temperature, pH, turbidity, electrical electrical conductivity, and phycocyanin. Total nitrogen (TN), full dissolved nitrogen (TDN), ammonium (NH4 +), total phosphorus (TP), total dissolved phosphorus (TDP), orthophosphate (PO4 3–), and chlorophyll a (Chl-a) were measured using standard methods (S1 Table). RNA extraction, sequencing: quality control details can be found in previous publications [4, xx–22]. A step by step protocol can be found at protocols.io describing the MoBio Powerwater Deoxyribonucleic acid kit used to excerpt RNA and all modifications to the manufacturer protocol [23]. The resulting textile paired-stop sequences of 125 bp were generated at Hudson Blastoff (Huntsville, AL, U.s.a.). Sequences are available from the MG-RAST database ("Lake_ Taihu_metatranscriptome_project"). Trimmed sequences from each sample were then combined to create a unmarried assembly using MegaHit [22, 24].
Microcystis spp. flower.
Image of the cyanobacterial community, dominated by Microcystis spp., from Taihu, China. Photograph was taken during one of the sampling expeditions (October 7, 2014). Photo credit: SW Wilhelm.
Host and virus detection
Genes of involvement were identified and quantified using a hallmark cistron arroyo previously described [25]. Briefly, our combined assembly was queried against a BLASTX 5.2.6.0+ database containing hallmark protein sequences from isolated reference genomes. Microcystis host species were identified using the DNA-dependent RNA polymerase (rpoB) and Microcystis phage were identified using the phage terminase (S2 Tabular array). The toxin encoding protein McyA was too used to characterize toxin product by Microcystis hosts and other cyanobacteria [26]. Sequences with BLASTX hits were considered candidates if they had an due east-value of less than eastward-30 or e-10 (for hosts and viruses respectively), were greater than 300 bp, and were less than 95% like to any other candidate [22].
Host and virus taxonomy
Microcystis host (RpoB and McyA) and virus candidate taxonomy was confirmed by placing the respective sequences on PhyML generated reference protein base phylogenetic copse using pplacer and visualized using iTOL v.4 [22, 27, 28]. All trees used to determine taxonomy are shown equally cladograms to resolve taxonomy into distinct groups (Fig two, S1 and S2 Figs). Microcystis spp. candidate sequences were showtime distinguished from other prokaryotes using a broad phylogenetic tree containing many prokaryotes and eukaryotes and then farther characterized to species and genotype [22]. The Microcystis species-specific RpoB tree contained numerous isolates to increase genetic resolution. Approximate viral taxonomy was established past querying the candidates against the NCBI RefSeq not-redundant database, removing whatever fake-positives or not-phage hits. The terminase tree for viruses independent many isolated viruses, both infecting and not infecting Microcystis and several virome sequences that originated from a Microcystis bloom and appeared in our BLASTX to the RefSeq database [29]. Inside these, three groups were considered specific to Microcystis. The first contains the Myoviridae strains Ma-LMM01, MaMV-DC, and Node 34. Ma-LMM01 and MaMV-DC are lab isolates known to infect Microcystis hosts, and Node 34 is an uncultured phage sequence from a Microcystis flower virome that is 99% similar to Ma-LMM01 and MaMV-DC [29–31]. The 2nd group, referred to as Sipho I, is an unusual grouping with no isolated phage known to infect Microcystis. Notwithstanding, this group contains the Siphoviridae prophage-similar sequence from Microcystis aeruginosa NIES-88 as well equally Node 382, another uncultured phage from the Morimoto et al. virome [29]. Because these viral terminase sequences are 98.5% similar and found both in the environment and in a Microcystis host genome, we assume that this is a previously disregarded phage capable of infecting Microcystis hosts. Node 331 was not included in this grouping, as it is only 56% like. The third group, referred to as Sipho II, contains the recently discovered Siphoviridae phage, Mic1 [32].
Expression of Microcystis genotypes.
Microcystis DNA-dependent RNA polymerase (RpoB) cladogram of genotypes, colored past phylogenetic grouping. Genotypes then rearranged based on temporal stage, with heatmap of the average full expression of each genotype. Bar charts stand for the average total expression for each genotype and each month. Red dots indicate no expression.
Host and virus activity
Transcript action was quantified by recruiting trimmed reads to candidate contigs that were trimmed to the length of the aligned hallmark cistron and normalized to the trimmed contig length and library size [22, 33]. Monthly expression patterns were visualized using Heatmapper and the average expression of each genotype per month [34]. Genotypes were classified as early, abiding, or late based on their patterns of average expression per month. Early genotypes displayed over 50% of their total expression during the months of June and July. Late genotypes displayed over 75% of their total expression during the months of August, September, and October. Constant genotypes did non have any month display higher than 25% of their total expression. The depiction betwixt early and late months was originally proposed in Tang et al., based on changes in nutrient conquering genes in the same dataset [4]. Pearson correlations between host and virus genotypes were established and visualized using RStudio. Correlations were corrected for multiple comparisons using the Benjamini Hochberg procedure [35]. Environmental drivers of host genotypic patterns were analyzed using canonical correspondence analysis (CCA) in RStudio.
Novel virus detection
In our primary analysis, we noticed a high similarity between several phage transcripts (tail sheath, terminase, major capsid protein) and sequences including in a published Microcystis host genome, NIES-88 when performing BLASTX [36]. Intrigued, we ran the host genome through Phaster [37] and discovered a prophage-like portion. This portion of the genome was then annotated using OmicsBox 5.1.ii.4 (BioBam, Valencia, Spain) and visualized using CG View (S3 Fig) [38].
Results
The Microcystis community
Our species-specific Microcystis RpoB cladogram indicated that 47 of the 52 candidates previously identified by Pound et al. (2020) were Microcystis (Fig two). The other five contigs originated from other cyanobacterial species. The most arable (total reads) Microcystis species were Microcystis flos-aquae and Microcystis wesenbergii, with 43.5% and 42.4%, respectively, of the total Microcystis spp. expression. These species likewise had the highest number of genotypes, with twenty One thousand. flos-aquae and 15 M. wesenbergii. Simply 4 genotypes of M. aeruginosa were observed, and these accounted for only ~seven.three% of the total Microcystis spp. expression. The classification of early, abiding, and late genotypes varies in species composition, with no obvious delineation or temporal shift in species (Fig 2). The early genotypes account for 59.seven% of the total expression, while the constant and late genotypes account for 27.ii% and 13.two%, respectively. In parallel, a total of thirty McyA candidate contigs were identified: 24 most closely related to diverse Microcystis species, and vi most closely related to other microcystin-producing cyanobacterial species (S1 Fig).
Microcystis-infecting viruses
Our method yielded 52 phage terminase candidates, 15 of which were adamant to be Microcystis specific (S2 Fig). Seven genotypes were almost closely related to the well-documented Myoviridae phages, Ma-LMM01 and Ma-MVDC [30, 31]. The Myoviridae group represented 22.four% of the total Microcystis-associated phage expression. Simply 1 candidate was about closely related to the Sipho I grouping containing our proposed novel phage, representing only 1.5% of the total Microcystis phage expression. The Sipho 2 group, containing Mic1, was the near arable, with vii genotypes accounting for 76.1% of the total Microcystis phage expression. However, most of that expression came from just two genotypes and occurred in Oct.
Seasonal shifts in expression
Pearson correlations indicated distinct seasonal patterns in expression of Microcystisinfecting phage also as toxin production genes (Fig three). Early Microcystis rpoB genotypes prove a positive correlation to the Myoviridae phage group, but negative correlations to both Siphoviridae groups. The changed is true in the tardily genotypes, when rpoB expression is negatively correlated to the Myoviridae group and positively correlated to both Siphoviridae groups. Correlation patterns with phage in the constantly expressed genotypes are less defined but show an inverse correlation to the Sipho I group and no significant correlation to the Sipho Two grouping.
Host and phage correlation analysis.
Pearson correlation analysis heatmap of Microcystis Deoxyribonucleic acid-dependent RNA polymerase (rpoB) genotypes correlated to Microcystis phage terminase genotypes and Microcystis toxin genotypes. Bluish indicates a meaning positive correlation between expression values and ruby-red indicates a pregnant negative correlation betwixt expression values. White indicates no significant correlations.
Correlation patterns of Microcystis rpoB and mcyA are similarly delineated by early, abiding, and belatedly rpoB genotypes (Fig 3). Early rpoB genotypes showed a negative human relationship to toxin-encoding gene expression, while constant and belatedly genotypes are positively correlated with toxin-encoding gene expression. mcyA expression is an boilerplate of two.1x higher in the late months (August, September, and Oct) than it is in the early months, indicating that early on genotypes display decreased expression of the microcystin encoding cistron, while belatedly genotypes display increased expression of the microcystin encoding cistron.
Environmental variables
To determine why rpoB genotypes take resolved into early, constant, and late groups, nosotros used a canonical correspondence analysis to orient the proportional expression of all rpoB genotypes in each of our 33 samples. CCA1 described 66.two% of the variation in our samples, while CCA2 described 6.two% of the variation. Of the ecology variables measured, sample month and pH were the most positively associated variables to CCA1 (Fig 4) (S1 Table). Electric conductivity, salinity, and total dissolved solids were too strongly associated with CCA1, in a negative management. Total dissolved nitrogen and ammonium concentrations were the most highly correlated variables to the secondary axis, CCA2.
Approved correspondence assay.
Canonical correspondence analysis of the proportional expression of all 47 Microcystis Deoxyribonucleic acid-dependent RNA polymerase (rpoB) genotypes in each of our 33 samples. Colour gradient indicates the pH of each sample.
Give-and-take
Cyanobacterial harmful algal blooms are a growing concern around the globe, and thus how they manifest–both in terms of function(s) and who is conduct out these functions (i.e., which strains or species) is of critical importance to their direction. The growing availability of genomic sequences has created opportunities for rapid cess of environmental genomes and transcriptomes using approaches that involve "recruitment" (i.e., mapping of the unknown environmental sequences to well-studied lab isolates). Yet, while these approaches take been valuable to engagement and taught u.s.a. much about how blooms are constrained, they are dependent on the choice of microbial strain for comparing. To move beyond these limits, nosotros have developed a workflow to characterize the subtle variations in multifariousness that are commonly disregarded within genera that cause these events. Given that lab strains of Microcystis represent a broad spectrum of genetic potentials that could skew observations in the to a higher place approach, our approach creates an opportunity to more than broadly capture spatial and temporal variation in Microcystis cell function in situ as multiple morphotypes and species are captured. When paired with parallel analyses of active viral infection of cells and toxin gene expression, a pic emerges that amend resolves the variability that occurs in nature. The genotypic diversity present in Lake Tai reveals important features of Microcystis bloom dynamics in this system. Our findings propose that the dominant species in the flower are M. flos-aquae and M. wesenbergii, not K. aeruginosa. Our observations confirm other studies which employed PCR-based approaches to characterize toxic communities [39–41] in concluding that Yard. flos-aquae and Thou. wesenbergii were common in Lake Tai. Our observations further testify a relationship between the distribution of subsets of these strains, transcription of toxin-encoding genes in the mcy cassette and active infections by dsDNA-phage idea to target Microcystis. In examining these data, we demonstrate how environmental atmospheric condition—in this instance pH—may play a role in promoting or constraining the interactions between flower success, viral infection and the product of a potent hepatotoxin. Taken together our observation begin to shed lite on the complex interactions that outcome in the proliferation of a different genera with a big cyanobacterial bloom.
Much cognition in microbiology stems from the use of lab cultures to mimic weather found in the environment. To appointment, most studies in both the lab and natural systems have been performed with M. aeruginosa due to the broad availability of isolates too as its implicit office every bit a major cyanotoxin producer in situ. Notwithstanding, our data suggest these strains may not provide the about authentic representation of bloom biomass in Lake Tai, nor flower response to perturbations [42–44], equally M. aeruginosa are only a subset (~ 7.three% of Microcystis spp. expression) of that community. Chiliad. aeruginosa NIES-843 was the first Microcystis species to take its genome fully-sequenced and closed [45], and therefore information technology has been the about widely applied genomic model for Microcystis blooms. Equally molecular biology becomes more broadly applied in natural systems, information technology is important to remember that an isolated reference organism may misrepresent the true diversity/function in a system. Every bit our approach revealed 47 genotypes including at least five separate species of Microcystis, this work shows that going forwards the utilise of a unmarried reference genome could obscure the different patterns of seasonal expression we observed across genotypes.
Our analyses revealed that the Microcystis genotypes demonstrated different patterns of expression over the course of the bloom. There was a strict delineation between early on and late genotypes, with additional genotypes occurring throughout the course of our sampling. These phases were initially characterized by Tang et al. (2018) as blossom "germination" and "maintenance". They suggested these temporal groups were associated with changes in food utilization strategies, based on temporal changes in the expression of nitrogen and phosphorus send genes that matched the temporal patterns we observed in genotype expression within the same dataset [four]. From our observations, we now believe that the changes observed in nutrient utilization may have been, in part, a byproduct of the shifting genotypic composition. Unfortunately, it is impossible to separate cause and outcome and it has go clear in recent years that food concentrations measured in conjunction with biological parameters are as much the residual (equally opposed to the cause) of the biological science that is present [46]. We notation that the temporal shift in genotypic populations does non indicate a morphospecies succession pattern. All 3 temporal groups are comprised of multiple Microcystis species, with no definitive dominance of any item morphospecies in a given temporal group (Fig 2). This suggests that the diverse species present might occupy parallel, still different functional niches within the ecosystem, allowing for co-occurring species groups [6]. This further suggests that attributions of functions to morphospecies may be inexact.
In improver to the 47 Microcystis genotypes nosotros observed, nosotros besides noted a wide diversity of Microcystis phages. In a parallel to efforts to recruit to Microcystis genomes, most literature pertaining to Microcystis phages refer only ii isolated Myoviridae phages, Ma-LMM01 and MaMV-DC [21, xxx, 31, 47] and uses these equally recruitment models. In the current study, our arroyo allowed us to detect these well-characterized Myoviridae phages, the newly characterized Siphoviridae phage, Mic1 [32], as well as a new Siphoviridae phage that we are confident infects Microcystis spp. This latter phage was originally "discovered" in our analyses of a genomic DNA scaffold of M. aeruginosa NIES-88, suggesting that it might have lysogenic potential (S3 Fig). Indeed, the genetic complement of this virus includes an integrase gene, which has not been observed in other Microcystis phages, although many have suggested the potential for lysogeny in Microcystis bloom systems [21, 48]. This NIES-88 phage portion does not appear to exist a consummate phage, indicating that it is likely remnant textile. The presence of this phage in the host genome promotes questions regarding the role of these viruses in horizontal gene transfer and the rate at which phage and host genomes commutation fabric: there is a definite precedent for this existence a common occurrence in filamentous cyanobacteria [49].
Just as the factor expression of our host genotypes resolved into three temporal groups, our 3 main classes of Microcystis phages did the same. The early phase of the bloom (June and July) was characterized by and over-representation of the Myoviridae phage transcripts, which had been observed previously [21]. Stough et al. used a single reference genome as bait to identify phage activity, yet in our effort nosotros have shown that there were seven genotypes present. The presence of multiple Myoviridae genotypes has been observed before via existent-time PCR and might propose rapid co-development with the host, or standing diversity [50]. While Ma-LMM01 and MaMV-DC were both originally isolated on M. aeruginosa, recent analysis of MaMV-DC indicates that it tin can limit the growth of Thou. wesenbergii and M. flos-aquae, although it did non grade plaques [51]. This suggests that the Myoviridae genotypes we observed may infect several Microcystis strains / species that were prominent in the spring. When the Myoviridae is highly expressed with the early on host genotypes, infection past the 2 Siphoviridae groups are about absent. In fact, the single Sipho I genotype was not expressed at all during June or July, and four of the seven Sipho II genotypes were not expressed at all during June. Sipho II was much more highly correlated to the belatedly host genotypes, when there was a subtract in lytic Myoviridae expression. This shift could exist explained in a number of means. The genotypic shift in hosts may reverberate a shift in host susceptibility or viral specificity [fifty] or a successional overturn, either through density-dependent infection or lysogenic reproduction [21, 52]. Nevertheless, it is important to note that Stough et al. observed an increase in genes associated with myocyanophage-lysogeny during the later months, when the belatedly genotypes are expressed [21]. It is possible that the Siphoviridae phages only get active once the Myoviridae phage have shifted into a lysogenic reproductive cycle. Or, information technology might be that the shift to a lysogeny for the Myoviridae might forestall superinfection, causing a decrease in the expression of lytic Myoviridae. In any case, it is unclear whether the host or the viruses are driving the temporal patterns nosotros find.
The early host genotypes that strongly correlated to Myoviridae expression besides strongly correlated (negatively) to the expression of the toxin coding mcyA gene. The constant and late genotypes are positively correlated with the expression of the toxin gene, even though actual toxin levels seem to decrease at the warmer temperatures typical of September and Oct [53]. Many studies have attempted to characterize genotypes and how toxin genes modify in copy abundance over the course of a bloom [14, 15, 54]. Expression of mcyA occurs throughout the flower, although there is an increase in the subsequently months, providing a positive correlation to both the abiding and late genotypes (S1 Fig). We note that over again at that place is a disconnect between phylogeny and temporal patterns, given the diverse composition of mcyA taxonomic groups. Microcystin production is thought to rarely issue from a single species or strain, but probable is a product of many co-occurring organisms [14, 16, nineteen]. Indeed, Otten and Paerl warn against using Microcystis species type to guess toxicity, considering the co-occurring presence of many species of various toxicities can obscure toxicity associations with detail species [twoscore]. Even the expression of the mcyA toxin-encoding gene (or whatever gene in that cassette) is non a guarantee that an organism is capable or actively producing microcystin, as oftentimes other components of the cassette can be missing [55].
Although toxin factor expression and viral infection show similar temporal patterns, this does not suggest that they are straight related or regulated. More than likely, both observations are a function of cellular processes responding to like external perturbations. Given that taxonomy is not capable of describing host activity, viral infection, or toxin gene expression, it is logical to hypothesize that the surroundings must be selecting for the genotypes nosotros observed during various bloom phases. While previous studies have proposed that fourth dimension of day could influence phage expression levels, we did non discover any design associated with diel cycling [vis a vis 29]. Our analyses revealed that one the primary ecology factor associated with the temporal shift in host rpoB expression was pH (Fig iv). System pH during cyanobacterial blooms is thought to increase due to the consumption of h2o cavalcade dissolved carbon dioxide. In parallel with this, pH is thought to influence Microcystis spp. carbon concentrating mechanisms, with evidence that Microcystis spp. are able to maintain growth at higher pH [56, 57]. It is unclear how pH may exist influencing toxicity or viral infection, although we hypothesize that linkages to photosynthesis, oxidative stress and food conquering are all potentially involved [56]. Electrical conductivity and salinity were also strongly associated with the temporal shift in host rpoB expression. These ii environmental parameters are highly cocky-correlated, representing the presence of sodium ions in the h2o. Combined with the strong clan of total dissolved solids, nosotros posit that this represents the presence of external terrestrial loading or resuspension, a hypothesis previously suggested by Wilhelm et al. [58]. This could also help explain why we do not observe a strong clan with our nutrient parameters such as nitrogen or phosphorus. They are likely beingness turned over quickly by the biological population, particularly during the early months of the productive bloom, whereas sodium ions would remain in the water column.
Overall, our observations accept allowed us to identify and quantify the abundant host and viral genotypes present in a freshwater cyanobacterial flower system across a temporal profile. A major ascertainment here is that the "bloom" does non appear to exist a single genotype of i organism, just at least 47 different phylotypes that come from multiple species of the same genus. Temporal shifts in agile viral infection (including transitions in the type of virus) and the expression of a primal factor for toxin product ostend that the metabolism of Microcystis is likely regulated by a complex interaction with environmental drivers [43] and that these drivers influence the style researchers translate flower dynamics [46]. Our study highlights the complexity of blossom systems, and how environmental factors can vary and relate to similar organisms in different ways.
Supporting information
S1 Fig
McyA cladogram.
Cladogram of toxin-encoding candidate contigs (mcyA). Inner color ring indicates taxonomic group and outer heatmap rings betoken the boilerplate expression of each candidate per month. Black dots bespeak bootstrap values greater than 0.5 and red dots point no expression.
(TIF)
S2 Fig
Terminase cladogram.
Cladogram of phage terminase candidate contigs. Inner colour ring indicates Microcystis phage grouping and outer heatmap rings bespeak the average expression of each candidate per calendar month. Black dots point bootstrap values greater than 0.5 and red dots indicate no expression.
(TIF)
S3 Fig
NIES-88 genome.
Genome scaffold map of NIES-88 (Accession number NZ_JXYX010000002). Orange open reading frames indicate phage-like genes.
(TIFF)
S1 Tabular array
Environmental parameters.
Tabular array of environmental parameters measured with each sample nerveless and the associated biplot scores for the RpoB approved correspondence analysis.
(XLSX)
S2 Table
Genotype sequences.
Sequences of RpoB, McyA, and terminase genotypes identified and analyzed.
(XLSX)
Acknowledgments
We thank Gary LeCleir, Robbie Martin, Eric Gann, Naomi Gilbert, Brittany Zepernick, Liz Denison and Gwen Stark for feedback and conversations on this topic.
Funding Statement
This piece of work was supported by funds from the National Science Foundation (IOS- 1451528 to SWW), and funding from the NIEHS (1P01ES028939–01) and NSF (OCE-1840715) to SWW through the Great Lakes Eye for Fresh Waters and Human Wellness at Bowling Green State Academy. We besides admit back up from the Simons Foundation (735077) and the Kenneth & Blaire Mossman Endowment to The University of Tennessee. The funders had no function in study design, information drove and analysis, decision to publish, or training of the manuscript.
Data Availability
Sequences are available from the MG-RAST database ("Lake_Taihu_metatranscriptome_project").
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