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At least 37 records · Page 2

Characterization of Two Microbial Isolates from Andean Lakes in Bolivia

We are currently investigating the biological population present in the highest and least explored perennial lakes on earth in the Bolivian and Chilean Andes, including several volcanic crater lakes of more than 6000 m elevation, in combination of microbiological and molecular biological methods. Our samples were collected in saline lakes of the Laguna Blanca Laguna Verde area in the Bolivian Altiplano and in the Licancabur volcano crater (27 deg. 47 min S/67 deg. 47 min. W) in the ongoing project studying high altitude lakes. The main goal of the project is to look for analogies with Martian paleolakes. These Bolivian lakes can be described as Andean lakes following the classification of Chong. We have attempted to isolate pure cultures and phylogenetically characterize prokaryotes that grew under laboratory conditions. Sediment samples taken from the Licancabur crater lake (LC), Laguna Verde (LV), and Laguna Blanca (LB) were analyzed and cultured using enriched liquid media under both aerobic and anaerobic conditions. All cultures were incubated at room temperature (15 to 20 C) and under light exposure. For the reported isolates, 36 hours incubation were necessary for reaching optimal optical densities to consider them viable cultures. Ten serial dilutions starting from 1% inoculum were required to obtain a suitable enriched cell culture to transfer into solid media. Cultures on solid medium were necessary to verify the formation of colonies in order to isolate pure cultures. Different solid media were prepared using several combinations of both trace minerals and carbohydrates sources in order to fit their nutrient requirements. The microorganisms formed individual colonies on solid media enriched with tryptone, yeast extract and sodium chloride. Cells morphology was studied by optical and electronic microscopy. Rodshape morphologies were observed in most cases. Total bacterial genomic DNA was isolated from 50 ml late-exponential phase culture by using the CTAB miniprep protocol. The 16S rRNA genes were amplified by PCR using both Bacteria- and Archaeauniversal primer sets: 27f and 1492r, 21f and 1492r respectively. Sequences of 16S rRNA gene were determined and initially compared with reference sequences contained in the EMBL nucleotide sequence database by using the BLAST program and were subsequently aligned with 16S rRNA reference sequences in the ARB package (http://www.mikro.biologie.tu-muenchen.de). Aligned sequences were inserted within a stable phylogenetic tree by using the ARB parsimony tool. In this work we report the morphology and phylogenetic characterization of two isolates belonged to Laguna Blanca sediments.

Demergasso, C.↗

Archaeal phylogeny: reexamination of the phylogenetic position of Archaeoglobus fulgidus in light of certain composition-induced artifacts

A major and too little recognized source of artifact in phylogenetic analysis of molecular sequence data is compositional difference among sequences. The problem becomes particularly acute when alignments contain ribosomal RNAs from both mesophilic and thermophilic species. Among prokaryotes the latter are considerably higher in G + C content than the former, which often results in artificial clustering of thermophilic lineages and their being placed artificially deep in phylogenetic trees. In this communication we review archaeal phylogeny in the light of this consideration, focusing in particular on the phylogenetic position of the sulfate reducing species Archaeoglobus fulgidus, using both 16S rRNA and 23S rRNA sequences. The analysis shows clearly that the previously reported deep branching of the A. fulgidus lineage (very near the base of the euryarchaeal side of the archaeal tree) is incorrect, and that the lineage actually groups with a previously recognized unit that comprises the Methanomicrobiales and extreme halophiles.

NASA Discipline Exobiology↗

Rooting the archaebacterial tree: the pivotal role of Thermococcus celer in archaebacterial evolution

The sequence of the 16S ribosomal RNA gene from the archaebacterium Thermococcus celer shows the organism to be related to the methanogenic archaebacteria rather than to its phenotypic counterparts, the extremely thermophilic archaebacteria. This conclusion turns on the position of the root of the archaebacterial phylogenetic tree, however. The problems encountered in rooting this tree are analyzed in detail. Under conditions that suppress evolutionary noise both the parsimony and evolutionary distance methods yield a root location (using a number of eubacterial or eukaryotic outgroup sequences) that is consistent with that determined by an "internal rooting" method, based upon an (approximate) determination of relative evolutionary rates.

Non-NASA Center↗

Combining biomarker and virus phylogenetic models improves HIV-1 epidemiological source identification

To identify and stop active HIV transmission chains new epidemiological techniques are needed. Here, we describe the development of a multi-biomarker augmentation to phylogenetic inference of the underlying transmission history in a local population. HIV biomarkers are measurable biological quantities that have some relationship to the amount of time someone has been infected with HIV. To train our model, we used five biomarkers based on real data from serological assays, HIV sequence data, and target cell counts in longitudinally followed, untreated patients with known infection times. The biomarkers were modeled with a mixed effects framework to allow for patient specific variation and general trends, and fit to patient data using Markov Chain Monte Carlo (MCMC) methods. Subsequently, the density of the unobserved infection time conditional on observed biomarkers were obtained by integrating out the random effects from the model fit. This probabilistic information about infection times was incorporated into the likelihood function for the transmission history and phylogenetic tree reconstruction, informed by the HIV sequence data. To critically test our methodology, we developed a coalescent-based simulation framework that generates phylogenies and biomarkers given a specific or general transmission history. Testing on many epidemiological scenarios showed that biomarker augmented phylogenetics can reach 90% accuracy under idealized situations. Under realistic within-host HIV-1 evolution, involving substantial within-host diversification and frequent transmission of multiple lineages, the average accuracy was at about 50% in transmission clusters involving 5–50 hosts. Realistic biomarker data added on average 16 percentage points over using the phylogeny alone. Using more biomarkers improved the performance. Shorter temporal spacing between transmission events and increased transmission heterogeneity reduced reconstruction accuracy, but larger clusters were not harder to get right. More sequence data per infected host also improved accuracy. We show that the method is robust to incomplete sampling and that adding biomarkers improves reconstructions of real HIV-1 transmission histories. The technology presented here could allow for better prevention programs by providing data for locally informed and tailored strategies.

60 APPLIED LIFE SCIENCES↗

Description and Genome Characterization of Three Novel Fungal Strains Isolated from Mars 2020 Mission-Associated Spacecraft Assembly Facility Surfaces—Recommendations for Two New Genera and One Species

National Aeronautics and Space Administration’s (NASA) spacecraft assembly facilities are monitored for the presence of any bacteria or fungi that might conceivably survive a transfer to an extraterrestrial environment. Fungi present a broad and diverse range of phenotypic and functional traits to adapt to extreme conditions, hence the detection of fungi and subsequent eradication of them are needed to prevent forward contamination for future NASA missions. During the construction and assembly for the Mars 2020 mission, three fungal strains with unique morphological and phylogenetic properties were isolated from spacecraft assembly facilities. The reconstruction of phylogenetic trees based on several gene loci (ITS, LSU, SSU, RPB, TUB, TEF1) using multi-locus sequence typing (MLST) and whole genome sequencing (WGS) analyses supported the hypothesis that these were novel species. Here we report the genus or species-level classification of these three novel strains via a polyphasic approach using phylogenetic analysis, colony and cell morphology, and comparative analysis of WGS. The strain FJI-L9-BK-P1 isolated from the Jet Propulsion Laboratory Spacecraft Assembly Facility (JPL-SAF) exhibited a putative phylogenetic relationship with the strain Aaosphaeria arxii CBS175.79 but showed distinct morphology and microscopic features. Another JPL-SAF strain, FJII-L3-CM-DR1, was phylogenetically distinct from members of the family Trichomeriaceae and exhibited morphologically different features from the genera Lithohypha and Strelitziana. The strain FKI-L1-BK-DR1 isolated from the Kennedy Space Center facility was identified as a member of Dothideomycetes incertae sedis and is closely related to the family Kirschsteiniotheliaceae according to a phylogenetic analysis. The polyphasic taxonomic approach supported the recommendation for establishing two novel genera and one novel species. The names Aaosphaeria pasadenensis (FJI-L9-BK-P1 = NRRL 64424 = DSM 114621), Pasadenomyces melaninifex (FJII-L3-CM-DR1 = NRRL 64433 = DSM 114623), and Floridaphiala radiotolerans (FKI-L1-BK-DR1 = NRRL 64434 = DSM 114624) are proposed as type species. Furthermore, resistance to ultraviolet-C and presence of specific biosynthetic gene cluster(s) coding for metabolically active compounds are unique to these strains.

59 BASIC BIOLOGICAL SCIENCES↗

An investigation of irreproducibility in maximum likelihood phylogenetic inference

Phylogenetic trees are essential for studying biology, but their reproducibility under identical parameter settings remains unexplored. Here, we find that 3515 (18.11%) IQ-TREE-inferred and 1813 (9.34%) RAxML-NG-inferred maximum likelihood (ML) gene trees are topologically irreproducible when executing two replicates (Run1 and Run2) for each of 19,414 gene alignments in 15 animal, plant, and fungal phylogenomic datasets. Notably, coalescent-based ASTRAL species phylogenies inferred from Run1 and Run2 sets of individual gene trees are topologically irreproducible for 9/15 phylogenomic datasets, whereas concatenation-based phylogenies inferred twice from the same supermatrix are reproducible. Our simulations further show that irreproducible phylogenies are more likely to be incorrect than reproducible phylogenies. These results suggest that a considerable fraction of single-gene ML trees may be irreproducible. Increasing reproducibility in ML inference will benefit from providing analyses’ log files, which contain typically reported parameters (e.g., program, substitution model, number of tree searches) but also typically unreported ones (e.g., random starting seed number, number of threads, processor type).

59 BASIC BIOLOGICAL SCIENCES↗

Substitution Models of Protein Evolution with Selection on Enzymatic Activity

Abstract Substitution models of evolution are necessary for diverse evolutionary analyses including phylogenetic tree and ancestral sequence reconstructions. At the protein level, empirical substitution models are traditionally used due to their simplicity, but they ignore the variability of substitution patterns among protein sites. Next, in order to improve the realism of the modeling of protein evolution, a series of structurally constrained substitution models were presented, but still they usually ignore constraints on the protein activity. Here, we present a substitution model of protein evolution with selection on both protein structure and enzymatic activity, and that can be applied to phylogenetics. In particular, the model considers the binding affinity of the enzyme–substrate complex as well as structural constraints that include the flexibility of structural flaps, hydrogen bonds, amino acids backbone radius of gyration, and solvent-accessible surface area that are quantified through molecular dynamics simulations. We applied the model to the HIV-1 protease and evaluated it by phylogenetic likelihood in comparison with the best-fitting empirical substitution model and a structurally constrained substitution model that ignores the enzymatic activity. We found that accounting for selection on the protein activity improves the fitting of the modeled functional regions with the real observations, especially in data with high molecular identity, which recommends considering constraints on the protein activity in the development of substitution models of evolution.

Ferreiro, David↗

Phylogeny of marine Bacillus isolates from the Gulf of Mexico

The phylogeny of 11 pigmented, aerobic, spore-forming isolates from marine sources was studied. Forty-two biochemical characteristics were examined, and a 16S rDNA sequence was obtained for each isolate. In a phylogenetic tree based on 16S sequencing, four isolates (NRRL B-14850, NRRL B-14904, NRRL B-14907, and NRRL B-14908) clustered with B. subtilis and related organisms; NRRL B-14907 was closely related to B. amyloliquefaciens. NRRL B-14907 and NRRL B-14908 were phenotypically similar to B. amyloliquefaciens and B. pumilus, respectively. Three strains (NRRL B-14906, NRRL B-14910, and NRRL B-14911) clustered in a clade that included B. firmus, B. lentus, and B. megaterium. NRRL B-14910 was closely related phenotypically and phylogenetically to B. megaterium. NRRL B-14905 clustered with the mesophilic round spore-producing species, B. fusiformis and B. sphaericus; the isolate was more closely related to B. fusiformis. NRRL B-14905 displayed characteristics typical of the B. sphaericus-like organisms. NRRL B-14909 and NRRL B-14912 clustered with the Paenibacillus species and displayed characteristics typical of the genus. Only NRRL B-14851, an unusually thin rod that forms very small spores, may represent a new Bacillus species.

NASA Discipline Exobiology↗

Variation in Sphingomonas traits across habitats and phylogenetic clades

Whether microbes show habitat preferences is a fundamental question in microbial ecology. If different microbial lineages have distinct traits, those lineages may occur more frequently in habitats where their traits are advantageous. Sphingomonas is an ideal bacterial clade in which to investigate how habitat preference relates to traits because these bacteria inhabit diverse environments and hosts. Here we downloaded 440 publicly available Sphingomonas genomes, assigned them to habitats based on isolation source, and examined their phylogenetic relationships. We sought to address whether: (1) there is a relationship between Sphingomonas habitat and phylogeny, and (2) whether there is a phylogenetic correlation between key, genome-based traits and habitat preference. We hypothesized that Sphingomonas strains from similar habitats would cluster together in phylogenetic clades, and key traits that improve fitness in specific environments should correlate with habitat. Genome-based traits were categorized into the Y-A-S trait-based framework for high growth yield, resource acquisition, and stress tolerance. We selected 252 high quality genomes and constructed a phylogenetic tree with 12 well-defined clades based on an alignment of 404 core genes. Sphingomonas strains from the same habitat clustered together within the same clades, and strains within clades shared similar clusters of accessory genes. Additionally, key genome-based trait frequencies varied across habitats. We conclude that Sphingomonas gene content reflects habitat preference. This knowledge of how environment and host relate to phylogeny may also help with future functional predictions about Sphingomonas and facilitate applications in bioremediation.

59 BASIC BIOLOGICAL SCIENCES↗

The phylogenetic roots of addiction: compulsive drug seeking, natural and drug-sensitive reward, and the acquisition of learned habits

Our rational faculties permit us humans to maximize the utility of our actions. We perform a fundamental type of cost-benefit analysis in which we frame a problem, assign values to the different paths, and then choose from among a set of available options, the course that promises the most favorable outcome. So why then does addiction appear to be so impervious to the associated costs, so unaffected by undesired consequences, and ultimately so resistant to cognitive oversight? The answer may likely be found in the fact that the drivers for compulsive drug seeking and drug taking are located in affective brain circuits, circuits that are structured and patterned by learning with repeated activation. These deep processes exhibit significant resistance to control by our cognitive faculties. The general consensus is that addiction arises from mechanisms that overvalue the magnitude of reward, discount the associated risks, and thereby bias individuals towards compulsive pursuit of addictive drugs. Behavioral disruption and dependence appear to arise at the intersection of a number of connected but separate phenomena: expectations for the occurrence of specific events, behaviors that seek encounters with them, the ability to notice and learn nonrandom, co-occurring conditions, the prediction and valuation of consequences, the forming of enduring memories, and the drivers of focused behavior through compulsion, habits, and acquired routines. It is important to recognize that each one of these individual faculties are present and well developed across the entire phylogenetic tree of bilateral metazoans. The goal of this special volume is dedicated to exploring the degree to which inherent elements can account for addiction and addiction-associated phenomena. In much of the literature on addiction, the underlying processes are often viewed as distinctly mammalian, arising, in part, from the strong cognitive capacities of this taxon. Some phenomena may even be regarded to exist only in primates, or even solely in humans. This supposition arises from the fact that studies are conducted almost exclusively in mammals and primates, while evolutionary antecedents of the behavior are rarely considered. A more comprehensive perspective that examines drug reward and reinforcement in a wider range of organisms demonstrates that many of the component traits are actually well developed across the greater metazoan lineage, and they may well predate the emergence of a mammalian clade by a wide margin. The collection of papers assembled here supports the notion that the capacity to associate cues and quences has not arisen in mammals de novo. Rather, the neural mechanisms for detecting contingencies and for predicting future outcomes are very deeply rooted across broad phylogenetic divisions. Our understanding of an ability to associate paired events has been enriched by work in invertebrate preparations in both classical and operant conditioning scenarios [Cook and Carew, 1986, 1989a, 1989b]. The ability to learn allows us to connect cues and behavioral actions to their associated consequences. Pavlovian conditioning enriches surrounding cues with predictive value. Outcomes with positive valence generate appetitive responses and approach to the associated cues, while those perceived as aversive bring cue avoidance and withdrawal. Humans are not the only life forms capable of such short- and long-term modulations of behavior

59 BASIC BIOLOGICAL SCIENCES↗

Deep Learning and Likelihood Approaches for Viral Phylogeography Converge on the Same Answers Whether the Inference Model Is Right or Wrong

Abstract Analysis of phylogenetic trees has become an essential tool in epidemiology. Likelihood-based methods fit models to phylogenies to draw inferences about the phylodynamics and history of viral transmission. However, these methods are often computationally expensive, which limits the complexity and realism of phylodynamic models and makes them ill-suited for informing policy decisions in real-time during rapidly developing outbreaks. Likelihood-free methods using deep learning are pushing the boundaries of inference beyond these constraints. In this paper, we extend, compare, and contrast a recently developed deep learning method for likelihood-free inference from trees. We trained multiple deep neural networks using phylogenies from simulated outbreaks that spread among 5 locations and found they achieve close to the same levels of accuracy as Bayesian inference under the true simulation model. We compared robustness to model misspecification of a trained neural network to that of a Bayesian method. We found that both models had comparable performance, converging on similar biases. We also implemented a method of uncertainty quantification called conformalized quantile regression that we demonstrate has similar patterns of sensitivity to model misspecification as Bayesian highest posterior density (HPD) and greatly overlap with HPDs, but have lower precision (more conservative). Finally, we trained and tested a neural network against phylogeographic data from a recent study of the SARS-Cov-2 pandemic in Europe and obtained similar estimates of region-specific epidemiological parameters and the location of the common ancestor in Europe. Along with being as accurate and robust as likelihood-based methods, our trained neural networks are on average over 3 orders of magnitude faster after training. Our results support the notion that neural networks can be trained with simulated data to accurately mimic the good and bad statistical properties of the likelihood functions of generative phylogenetic models.

Evolutionary Biology↗

A deep learning approach to real-time HIV outbreak detection using genetic data

Pathogen genomic sequence data are increasingly made available for epidemiological monitoring. A main interest is to identify and assess the potential of infectious disease outbreaks. While popular methods to analyze sequence data often involve phylogenetic tree inference, they are vulnerable to errors from recombination and impose a high computational cost, making it difficult to obtain real-time results when the number of sequences is in or above the thousands. Here, we propose an alternative strategy to outbreak detection using genomic data based on deep learning methods developed for image classification. The key idea is to use a pairwise genetic distance matrix calculated from viral sequences as an image, and develop convolutional neutral network (CNN) models to classify areas of the images that show signatures of active outbreak, leading to identification of subsets of sequences taken from an active outbreak. We showed that our method is efficient in finding HIV-1 outbreaks with R0 ≥ 2.5, and overall a specificity exceeding 98% and sensitivity better than 92%. We validated our approach using data from HIV-1 CRF01 in Europe, containing both endemic sequences and a well-known dual outbreak in intravenous drug users. Our model accurately identified known outbreak sequences in the background of slower spreading HIV. Importantly, we detected both outbreaks early on, before they were over, implying that had this method been applied in real-time as data became available, one would have been able to intervene and possibly prevent the extent of these outbreaks. This approach is scalable to processing hundreds of thousands of sequences, making it useful for current and future real-time epidemiological investigations, including public health monitoring using large databases and especially for rapid outbreak identification.

59 BASIC BIOLOGICAL SCIENCES↗

Biogeographic patterns in populations of marine Pseudoalteromonas atlantica isolates

Intra-specific genomic diversity is well documented in microbes. The question, however, remains whether natural selection or neutral evolution is the major contributor to this diversity. We undertook this study to estimate genomic diversity in Pseudoalteromonas atlantica populations and whether the diversity, if present, could be attributed to environmental factors or distance effects. Here, we isolated and sequenced twenty-three strains of P. atlantica from three geographically distant deep marine basins and performed comparative genomic analyses to study the genomic diversity of populations among these basins. Average nucleotide identity followed a strictly geographical pattern. In two out of three locations, the strains within the location exhibited >99.5% identity, whereas, among locations, the strains showed <98.11% identity. Phylogenetic and pan-genome analysis also reflected the biogeographical separation of the strains. Strains from the same location shared many accessory genes and clustered closely on the phylogenetic tree. Phenotypic diversity between populations was studied in ten out of twenty-three strains testing carbon and nitrogen source utilization and osmotolerance. A genetic basis for phenotypic diversity could be established in most cases but was apparently not influenced by local environmental conditions. Our study suggests that neutral evolution may have a substantial role in the biodiversity of P. atlantica.

59 BASIC BIOLOGICAL SCIENCES↗

The success of particular Acinetobacter baumannii clones: accumulating resistance and virulence inside a sugary shield

Abstract Background In Portugal, carbapenem-resistant Acinetobacter baumannii (CRAB) has been associated with ST98, ST103 and ST208 (Oxford Scheme, Oxf) and a clone has usually been associated with a particular period of time. These clonal shifts were primarily explained by an increased antimicrobial resistance profile. Here we explore genomic and biochemical differences among these and more recent clones, which could further explain the diversity and evolution of this species. Methods A total of 116 CRAB isolates (2010–15), together with representatives of a previously described CRAB collection (4 isolates, 2001–06) were characterized by attenuated total reflection Fourier transform infrared spectroscopy (FTIR-ATR) and MLST. Representatives of different FTIR-ATR/MLST clusters were selected for WGS (n = 13), which allowed the in silico extraction of resistance and virulence genes, capsule locus and SNP analysis. Results A. baumannii clonal shifts of OXA-58-producing ST103Oxf (2001–04), OXA-40-producing ST98Oxf (2002–06), OXA-23-producing ST208Oxf (2006–10) and OXA-23-producing ST218Oxf (2010–15) were accompanied by an increase in AMR genes and virulence factors. FTIR-ATR clustering was congruent with sugar composition predicted from the capsular locus: a fucosamine cluster comprising ST98Oxf, ST103Oxf and a single ST218Oxf isolate; a pseudaminic acid cluster of ST208Oxf and ST1557Oxf isolates; and legionaminic acid, resembling the sialic acid from mammalian cells, in a cluster comprising ST218Oxf isolates. The whole-genome phylogenetic tree was congruent with MLST, with isolates presenting 5–28 938 SNPs. ST208Oxf and ST218Oxf presented ∼1900 SNPs while ST103Oxf and ST1557Oxf showed a greater number of SNPs (∼28 000). Conclusions Clonal shifts of CRAB were promoted, in our country, by consecutive virulence and AMR gene pool enlargement, together with features increasing pathogen–host adaptation. Worldwide dominance of ST218Oxf is supported by the combination of high AMR and virulence levels.

Silva, Liliana↗

Spirochaete genome identified in red abalone sample represents a novel genus Candidatus Haliotispira gen. nov. within the order Spirochaetales

A fully assembled spirochaete genome was identified as a contaminating scaffold in our red abalone ( Haliotis rufescens ) genome assembly. In this paper, we describe the analysis of this bacterial genome. The assembled spirochaete genome is 3.25 Mb in size with 48.5 mol% G+C content. The proteomes of 38 species were compared with the spirochaete genome and it was discovered to form an independent branch within the family Spirochaetaceae on the phylogenetic tree. The comparison of 16S rRNA sequences and average nucleotide identity scores between the spirochaete genome with known species of different families in Spirochaetia indicate that it is an unknown species. Further, the percentage of conserved proteins compared to neighbouring taxa confirm that it does not belong to a known genus within Spirochaetaceae . We propose the name Candidatus Haliotispira prima gen. nov., sp. nov. based on its taxonomic placement and origin. We also tested for the presence of this species in different species of abalone and found that it is also present in white abalone ( Haliotis sorenseni ). In addition, we highlight the need for better classification of taxa within the class Spirochaetia .

Microbiology↗

Phylogenetic analyses and reclassification of the oleaginous marine species Nannochloris sp. “desiccata" (Trebouxiophyceae, Chlorophyta), formerly Chlorella desiccata , supported by a high-quality genome assembly

Microalgae are diverse, with many gaps remaining in phylogenetic and physiological understanding. Thus, studying new microalgae species increases our broader comprehension of biological diversity, and evaluation of new candidates as algal production platforms can lead to improved productivity under a variety of cultivation conditions. Chlorella is a genus of fast-growing species often isolated from freshwater habitats and cultivated as a source of nutritional supplements. However, the use of freshwater increases competition with other freshwater needs. We identified Chlorella desiccata to be worthy of further investigation as a potential algae production strain, due to its isolation from a marine environment and its promising growth and biochemical composition properties. Long-read genomic sequencing was conducted for C. desiccata UTEX 2526, resulting in a high-quality, near chromosome level, diploid genome with an assembly length of 21.55 Mbp in only 18 contigs. We also report complete circular mitochondrial and chloroplast genomes. Phylogenomic and phylogenetic analyses using nuclear, chloroplast, 18S rRNA, and actin sequences revealed that this species clades within strains currently identified as Nannochloris (Trebouxiophyceae, Chlorophyta), leading to its reclassification as Nannochloris sp. “desiccata” UTEX 2526. The mode of cell division for this species is autosporulation, differing from the type species N. bacillaris. As has occurred across multiple microalgae genera, there are repeated examples of Nannochloris species reclassification in the literature. This high-quality genome assembly and phylogenetic analysis of the potential algal production strain Nannochloris sp. “desiccata” UTEX 2526 provides an important reference and useful tool for further studying this region of the phylogenetic tree.

59 BASIC BIOLOGICAL SCIENCES↗

OrthoPhylo

This software builds on PHAME developed at LANL to generate phylogenetic trees of bacterial whole genome sequences. Where PHAME uses whole genome alignments to generate informative sites to base tress on, PHAME-OuS annotates bacterial genes, identifies orthologous sequences, aligns related proteins, uses those alignments to inform transcript alignments, then builds trees with several methods. The first is a conventional gene concatenation and ML tree estemation method. The second attempts to reconcile gene tree with a unified species tree using quartets (ASTRAL). Both methods allow filtering of gene lists on number of species represented, length, and gappiness in order to tune noise-to-signal for tree estimation

Middlebrook, Earl↗

IMA genome-F18

Sequencing fungal genomes has now become very common and the list of genomes in this manuscript reflects this. Particularly relevant is that the first announcement is a re-identification of Penicillium genomes available on NCBI. The fact that more than 100 of these genomes have been deposited without the correct species names speak volumes to the fact that we must continue training fungal taxonomists and the importance of the International Mycological Association (after which this journal is named). When we started the genome series in 2013, one of the essential aspects was the need to have a phylogenetic tree as part of the manuscript. This came about as the result of a discussion with colleagues in NCBI who were trying to deal with the very many incorrectly identified bacterial genomes (at the time) which had been submitted to NCBI. We are now in the same position with fungal genomes. Sequencing a fungal genome is all too easy but providing a correct species name and ensuring that the fungus has in fact been correctly identified seems to be more difficult. We know that there are thousands of fungi which have not yet been described. The availability of sequence data has made identification of fungi easier but also serves to highlight the need to have a fungal taxonomist in the project to make sure that mistakes are not made.

59 BASIC BIOLOGICAL SCIENCES↗