The Ancient Origins of Death Domains Support the 'Original Sin' Hypothesis for the Evolution of Programmed Cell Death.

The discovery of caspase homologs in bacteria highlighted the relationship between programmed cell death (PCD) evolution and eukaryogenesis. However, the origin of PCD genes in prokaryotes themselves (bacteria and archaea) is poorly understood and a source of controversy. Whether archaea also contain C14 peptidase enzymes and other death domains is largely unknown because of a historical dearth of genomic data. Archaeal genomic databases have grown significantly in the last decade, which allowed us to perform a detailed comparative study of the evolutionary histories of PCD-related death domains in major archaeal phyla, including the deepest branching phyla of Candidatus Aenigmarchaeota, Candidatus Woesearchaeota, and Euryarchaeota. We identified death domains associated with executioners of PCD, like the caspase homologs of the C14 peptidase family, in 321 archaea sequences. Of these, 15.58% were metacaspase type I orthologues and 84.42% were orthocaspases. Maximum likelihood phylogenetic analyses revealed a scattered distribution of orthocaspases and metacaspases in deep-branching bacteria and archaea. The tree topology was incongruent with the prokaryote 16S phylogeny suggesting a common ancestry of PCD genes in prokaryotes and subsequent massive horizontal gene transfer coinciding with the divergence of archaea and bacteria. Previous arguments for the origin of PCD were philosophical in nature with two popular propositions being the "addiction" and 'original sin' hypotheses. Our data support the 'original sin' hypothesis, which argues for a pleiotropic origin of the PCD toolkit with pro-life and pro-death functions tracing back to the emergence of cellular life-the Last Universal Common Ancestor State.

Programmed cell death as a black queen in microbial communities.

Programmed cell death (PCD) in unicellular organisms is in some instances an altruistic trait. When the beneficiaries are clones or close kin, kin selection theory may be used to explain the evolution of the trait, and when the trait evolves in groups of distantly related individuals, group or multilevel selection theory is invoked. In mixed microbial communities, the benefits are also available to unrelated taxa. But the evolutionary ecology of PCD in communities is poorly understood. Few hypotheses have been offered concerning the community role of PCD despite its far-reaching effects. The hypothesis we consider here is that PCD is a black queen. The Black Queen Hypothesis (BQH) outlines how public goods arising from a leaky function are exploited by other taxa in the community. Black Queen (BQ) traits are essential for community survival, but only some members bear the cost of possessing them, while others lose the trait In addition, BQ traits have been defined in terms of adaptive gene loss, and it is unknown whether this has occurred for PCD. Our conclusion is that PCD fulfils the two most important criteria of a BQ (leakiness and costliness), but that more empirical data are needed for assessing the remaining two criteria. In addition, we hold that for viewing PCD as a BQ, the original BQH needs to include social traits. Thus, despite some empirical and conceptual shortcomings, the BQH provides a helpful avenue for investigating PCD in microbial communities.

Assessing computational genomics skills: Our experience in the H3ABioNet African bioinformatics network.

The H3ABioNet pan-African bioinformatics network, which is funded to support the Human Heredity and Health in Africa (H3Africa) program, has developed node-assessment exercises to gauge the ability of its participating research and service groups to analyze typical genome-wide datasets being generated by H3Africa research groups. We describe a framework for the assessment of computational genomics analysis skills, which includes standard operating procedures, training and test datasets, and a process for administering the exercise. We present the experiences of 3 research groups that have taken the exercise and the impact on their ability to manage complex projects. Finally, we discuss the reasons why many H3ABioNet nodes have declined so far to participate and potential strategies to encourage them to do so.

Robust sequence alignment using evolutionary rates coupled with an amino acid substitution matrix.

BACKGROUND: Selective pressures at the DNA level shape genes into profiles consisting of patterns of rapidly evolving sites and sites withstanding change. These profiles remain detectable even when protein sequences become extensively diverged. A common task in molecular biology is to infer functional, structural or evolutionary relationships by querying a database using an algorithm. However, problems arise when sequence similarity is low. This study presents an algorithm that uses the evolutionary rate at codon sites, the dN/dS (ω) parameter, coupled to a substitution matrix as an alignment metric for detecting distantly related proteins. The algorithm, called BLOSUM-FIRE couples a newer and improved version of the original FIRE (Functional Inference using Rates of Evolution) algorithm with an amino acid substitution matrix in a dynamic scoring function. The enigmatic hepatitis B virus X protein was used as a test case for BLOSUM-FIRE and its associated database EvoDB. RESULTS: The evolutionary rate based approach was coupled with a conventional BLOSUM substitution matrix. The two approaches are combined in a dynamic scoring function, which uses the selective pressure to score aligned residues. The dynamic scoring function is based on a coupled additive approach that scores aligned sites based on the level of conservation inferred from the ω values. Evaluation of the accuracy of this new implementation, BLOSUM-FIRE, using MAFFT alignment as reference alignments has shown that it is more accurate than its predecessor FIRE. Comparison of the alignment quality with widely used algorithms (MUSCLE, T-COFFEE, and CLUSTAL Omega) revealed that the BLOSUM-FIRE algorithm performs as well as conventional algorithms. Its main strength lies in that it provides greater potential for aligning divergent sequences and addresses the problem of low specificity inherent in the original FIRE algorithm. The utility of this algorithm is demonstrated using the Hepatitis B virus X (HBx) protein, a protein of unknown function, as a test case. CONCLUSION: This study describes the utility of an evolutionary rate based approach coupled to the BLOSUM62 amino acid substitution matrix in inferring protein domain function. We demonstrate that such an approach is robust and performs as well as an array of conventional algorithms.

Large-scale environmental signals in seagrass blue carbon stocks are hidden by high variability at local scales.

Increasing focus on nature-based climate change mitigation and adaptation strategies has led to the recognition of seagrasses as globally significant organic carbon (Corg) stocks. However, estimates of carbon stocks have been generally confined to a few regions, with few African studies represented in global datasets. In addition, the extent to which biogeographical and environmental variation shape carbon stocks in marine vegetated environments remains uncertain. For South Africa, Zostera capensis is the dominant seagrass species with limited mapping and quantification of its Corg stocks. Here, we measured Z. capensis Corg stocks at six South African estuaries spanning ∼1800 km of the cool-temperate to subtropical marine environmental gradient. Targeting the intertidal zone of the upper and lower estuary reaches, we collected Z. capensis sediments to a depth of 50 cm and measured the Corg, with the median Corg stock estimated at 24.11 Mg C ha-1 (40.4 ± 53.02; mean ± SD). While this is lower than the global average, these data demonstrate that Z. capensis ecosystems are important contributors to blue carbon stocks in the region. Measured Corg stocks showed significant differences between sampling sites for estuaries; however, we did not detect significant differences between estuaries due to high intra-estuarine Corg variability. Examination of biogeographical regions, terrestrial and marine environmental variables as drivers of Corg variability revealed that annual mean sea surface temperature may explain variation in Corg stocks. Furthermore, we found evidence of signals of biogeographical regions and precipitation driving some of the variability in Corg stocks; however, this requires further investigation. Overall, our estimates for Z. capensis add to ongoing national and global efforts to quantify seagrass Corg stocks across environmental and biogeographic gradients to better determine their contributions as nature-based solutions to climate change.

De novo assembly and annotation of the transcriptome of the endangered seagrass Zostera capensis: Insights from differential gene expression under thermal stress.

Seagrasses are important marine ecosystem engineers but anthropogenic impacts and climate change have led to numerous population declines globally. In South Africa, Zostera capensis is endangered due to fragmented populations and heavy anthropogenic pressures on estuarine ecosystems that house the core of the populations. Addressing questions of how pressures such as climate change affect foundational species, including Z. capensis are crucial to supporting their conservation and underpin restoration efforts. Here we use ecological transcriptomics to study key functional responses of Z. capensis through quantification of gene expression after thermal stress and present the first reference transcriptome of Z. capensis. Four de novo reference assemblies (Trinity, IDBA-tran, RNAspades, SOAPdenovo) filtered through the EvidentialGene pipeline resulted in 153,755 transcripts with a BUSCO score of 66.1% for completeness. Differential expression analysis between heat stressed (32 °C for three days) and pre-warming plants identified genes involved in photosynthesis, oxidative stress, translation, metabolic and biosynthetic processes in the Z. capensis thermal stress response. This reference transcriptome is a significant contribution to the limited available genomic resources for Z. capensis and represents a vital tool for addressing questions around the species restoration and potential functional responses to warming marine environments.

EvoDB: a database of evolutionary rate profiles, associated protein domains and phylogenetic trees for PFAM-A.

The evolutionary rate at codon sites across protein-coding nucleotide sequences represents a valuable tier of information for aligning sequences, inferring homology and constructing phylogenetic profiles. However, a comprehensive resource for cataloguing the evolutionary rate at codon sites and their corresponding nucleotide and protein domain sequence alignments has not been developed. To address this gap in knowledge, EvoDB (an Evolutionary rates DataBase) was compiled. Nucleotide sequences and their corresponding protein domain data including the associated seed alignments from the PFAM-A (protein family) database were used to estimate evolutionary rate (ω = dN/dS) profiles at codon sites for each entry. EvoDB contains 98.83% of the gapped nucleotide sequence alignments and 97.1% of the evolutionary rate profiles for the corresponding information in PFAM-A. As the identification of codon sites under positive selection and their position in a sequence profile is usually the most sought after information for molecular evolutionary biologists, evolutionary rate profiles were determined under the M2a model using the CODEML algorithm in the PAML (Phylogenetic Analysis by Maximum Likelihood) suite of software. Validation of nucleotide sequences against amino acid data was implemented to ensure high data quality. EvoDB is a catalogue of the evolutionary rate profiles and provides the corresponding phylogenetic trees, PFAM-A alignments and annotated accession identifier data. In addition, the database can be explored and queried using known evolutionary rate profiles to identify domains under similar evolutionary constraints and pressures. EvoDB is a resource for evolutionary, phylogenetic studies and presents a tier of information untapped by current databases.