Hsp70 duplication in the Drosophila melanogaster species group: how and when did two become five?

To determine how the modern copy number (5) of hsp70 genes in Drosophila melanogaster evolved, we localized the duplication events that created the genes in the phylogeny of the melanogaster group, examined D. melanogaster genomic sequence to investigate the mechanisms of duplication, and analyzed the hsp70 gene sequences of Drosophila orena and Drosophila mauritiana. The initial two-to-four hsp70 duplication occurred 10--15 MYA, according to fixed in situ hybridization to polytene chromosomes, before the origin and divergence of the melanogaster and five other species subgroups of the melanogaster group. Analysis of more than 30 kb of flanking sequence surrounding the hsp70 gene clusters suggested that this duplication was likely a retrotransposition. For the melanogaster subgroup, Southern hybridization and an hsp70 restriction map confirmed the conserved number (4) and arrangement of hsp70 genes in the seven species other than D. melanogaster. Drosophila melanogaster is unique; tandem duplication and gene conversion at the derived cluster yielded a fifth hsp70 gene. The four D. orena hsp70 genes are highly similar and concertedly evolving. In contrast, the D. mauritiana hsp70 genes are divergent, and many alleles are nonfunctional. The proliferation, concerted evolution, and maintenance of functionality in the D. melanogaster hsp70 genes is consistent with the action of natural selection in this species.     

Gas treatment in trickle-bed biofilters: biomass, how much is enough?

The objective of this article is to define and validate a mathematical model that desribes the physical and biological processes occurring in a trickle-bed air biofilter for waste gas treatment. This model considers a two-phase system, quasi-steady-state processes, uniform bacterial population, and one limiting substrate. The variation of the specific surface area with bacterial growth is included in the model, and its effect on the biofilter performance is analyzed. This analysis leads to the conclusion that excessive accumulation of biomass in the reactor has a negative effect on contaminant removal efficiency. To solve this problem, excess biomass is removed via full media fluidization and backwashing of the biofilter. The backwashing technique is also incorporated in the model as a process variable. Experimental data from the biodegradation of toluene in a pilot system with four packed-bed reactors are used to validate the model. Once the model is calibrated with the estimation of the unknown parameters of the system, it is used to simulate the biofilter performance for different operating conditions. Model predictions are found to be in agreement with experimental data. (c) 1997 John Wiley & Sons, Inc. Biotechnol Bioeng 54: 583-594, 1997.     

Integrating biology and economics in seagrass restoration: How much is enough and why?

Although success criteria for seagrass restoration have been in place for some time, there has been little consistency regarding how much habitat should be restored for every unit area lost (the replacement ratio). Extant success criteria focus on persistence, area, and habitat quality (shoot density). These metrics, while conservative, remain largely accepted for the seagrass ecosystem. Computation of the replacement ratio using economic tools has recently been integrated with seagrass restoration and is based on the intrinsic recovery rate of the injured seagrass beds themselves as compared with the efficacy of the restoration itself. In this application, field surveys of injured seagrass beds in the Florida Keys National Marine Sanctuary (FKNMS) were conducted over several years and provide the basis for computing the intrinsic recovery rate and thus, the replacement ratio. This computation is performed using the Habitat Equivalency Analysis (HEA) and determines the lost on-site services pertaining to the ecological function of an area as the result of an injury and sets this against the difference between intrinsic recovery and recovery afforded by restoration. Joining empirical field data with economic theory has produced a reasonable and typically conservative means of determining the level of restoration and this has been fully supported in Federal Court rulings. Having clearly defined project goals allows application of the success criteria in a predictable, consistent, reasonable, and fair manner.     

Genome scan methods against more complex models: when and how much should we trust them?

The recent availability of next‐generation sequencing (NGS) has made possible the use of dense genetic markers to identify regions of the genome that may be under the influence of selection. Several statistical methods have been developed recently for this purpose. Here, we present the results of an individual‐based simulation study investigating the power and error rate of popular or recent genome scan methods: linear regression, Bayescan, BayEnv and LFMM. Contrary to previous studies, we focus on complex, hierarchical population structure and on polygenic selection. Additionally, we use a false discovery rate (FDR)‐based framework, which provides an unified testing framework across frequentist and Bayesian methods. Finally, we investigate the influence of population allele frequencies versus individual genotype data specification for LFMM and the linear regression. The relative ranking between the methods is impacted by the consideration of polygenic selection, compared to a monogenic scenario. For strongly hierarchical scenarios with confounding effects between demography and environmental variables, the power of the methods can be very low. Except for one scenario, Bayescan exhibited moderate power and error rate. BayEnv performance was good under nonhierarchical scenarios, while LFMM provided the best compromise between power and error rate across scenarios. We found that it is possible to greatly reduce error rates by considering the results of all three methods when identifying outlier loci.     

Collagen-induced arthritis and related animal models: how much of their pathogenesis is auto-immune, how much is auto-inflammatory?

In this review, we discuss our studies on the pathogenesis of collagen-induced arthritis (CIA) and related mouse models for rheumatoid arthritis. Of note, these models invariably rely on the use of complete Freund's adjuvant (CFA). Our analysis has focused on explaining the dichotomous - either protective or disease-promoting - role of endogenous IFN-γ. Induction of a myelopoietic burst by CFA was identified as an important and underestimated factor in mediating the role of IFN-γ and other cytokines (IL-6, IL-17, GCP-2, RANK-L). Myelopoiesis provides an excess in precursors for joint-infiltrating neutrophils and osteoclasts. We postulate that classical CIA is primarily an auto-inflammatory disease, in part because of a strong innate immune response to the adjuvant. Superimposed on this, collagen-specific auto-immunity reinforces inflammatory reactivity in joints.     

The shape of life: how much is written in stone?

Considering the enormous diversity of living organisms, representing mostly untapped resources for studying ecological, ontogenetic and phylogenetic patterns and processes, why should evolutionary biologists concern themselves with the remains of animals and plants that died out tens or even hundreds of millions of years ago? The reason is that important new insights into some of the most vexing evolutionary questions are being revealed at the interfaces of palaeontology, developmental biology and molecular biology. Attempts to synthesise information from these disciplines, however, often encounter their greatest hurdles in considerations of the radiation of the Metazoa. Ongoing challenges relate to the origins of body plans, the relationships of the metazoan phyla and the timing of major evolutionary radiations. Palaeontology not only has its own unique contributions to the study of evolutionary processes, but provides a lynchpin for many of the emerging techniques.     

Variation in hominid brain size: how much is due to method?

Brain size represented by cranial capacity (CC) is one of the most frequently analysed characters of hominids. Accuracy of individual CC estimates depends on completeness of specimens and methods used for reconstruction and measurement. A file of published estimates of CC of hominids dated from 3.2 Ma (million years) to 10 Ka (thousand years) including 606 estimates for 243 specimens was compiled. In the file, 75 specimens are available with multiple values (3 to 15) obtained by various methods and/or by various authors. Using individuals as classes in ANOVA, intraclass variation, which represents "error" of estimates, was calculated. For the total sample of multiple estimates (N = 382) the error variance is 5315 ml2. The error standard deviation is 73 ml (coefficient of variation (CV = 7.3%), quite large in comparison to the actual variation in CC in modern humans, SD = 157 ml (CV = 11.6%). This large error makes us wonder whether any fossil can be reliably placed with respect to a particular "cerebral Rubicon" between palaeospecies. Recent discussions concerning cranial capacity of Stw505 are a case in point regarding errors in CC estimation. In actual repeated 30 time measurements on a research quality cast we obtained with various methods (water, seeds, plasticine) CC estimates ranging from 484 to 586 ml. The range of estimates in the literature is from 515 to 625 ml. When hominid CC by taxon with date as a covariate is subjected to ANOVA, taxon is responsible for 5% of the variance while date is responsible for the main portion, (89%). The relationship between CC and date is best characterised as a gradual time trend. It is proven by the ANOVA test for linearity, by gamma test for trend and by ASReml fitting of a linear function. The line of best fit to this time trend is a double exponential curve which explains 90% of the total variance in CC: CC = 306.63 (4.83(0.9995)DATE) Essentially the same curve fits subsamples of CC dated at less than 1 Ma and at 3.2-1.0 Ma. This has several implications for the nature of the Darwinian process to be reconstructed.     

Mesenchymal stromal cell therapy for coronavirus disease 2019: which? when? and how much?

Mesenchymal stromal cells (MSCs) are under active consideration as a treatment strategy for controlling the hyper-inflammation and slow disease progression associated with coronavirus disease 2019 (COVID-19). The possible mechanism of protection through their immunoregulatory and paracrine action has been reviewed extensively. However, the importance of process control in achieving consistent cell quality, maximum safety and efficacy—for which the three key questions are which, when and how much—remains unaddressed. Any commonality, if it exists, in ongoing clinical trials has yet to be analyzed and reviewed. In this review, the authors have therefore compiled study design data from ongoing clinical trials to address the key questions of “which” with regard to tissue source, donor profile, isolation technique, culture conditions, long-term culture and cryopreservation of MSCs; “when” with regard to defining the transplantation window by identifying and staging patients based on their pro-inflammatory profile; and “how much” with regard to the number of cells in a single administration, number of doses and route of transplantation. To homogenize MSC therapy for COVID-19 on a global scale and to make it readily available in large numbers, a shared understanding and uniform agreement with respect to these fundamental issues are essential.     

Phylogenetic inference: how much evolutionary history is knowable?

In order to reconstruct phylogenetic trees from extremely dissimilar sequences it is necessary to estimate accurately the extent of sequence divergence. In this paper a new method of sequence analysis, Markov triple analysis, is developed for determining the relative frequencies of nucleotide substitutions within the three branches of a three-taxon dendrogram. Assuming that nucleotide sites are independently and identically distributed and assuming a Markov model for nucleotide (or protein) evolution, it is shown that the unique Markov matrices can be reconstructed given only the joint probability distribution relating three taxa. (In the much simpler case involving only two taxa and two character states, Markov matrices can also be reconstructed, provided symmetry assumptions are placed on the elements of the matrices.) The method is illustrated using sequence data from the combined first and second codon positions derived from complete human, mouse, and cow mitochondrial sequences.      

The economy of inflammation: when is less more?

In ecology, tolerance of parasites refers to host mitigation of the fitness costs of an infection. This concept of parasite tolerance contrasts with resistance, whereby hosts reduce the intensity of an infection. Anti-inflammatory cells and molecules have been implicated as mechanisms of parasite tolerance, suggesting that a major role of tolerance is in minimizing collateral damage associated with inflammation. A framework is proposed here in which the cost-benefit outcome of an inflammatory host-response is hypothesized to be dependent on host life-history, parasite virulence, and the efficacy of a current inflammatory or anti-inflammatory response. Testable predictions, both within and among host species, are presented for this hypothesis.     

Y chromosome and other heterochromatic sequences of the Drosophila melanogaster genome: how far can we go?

Whole genome shotgun assemblies have proven remarkably successful in reconstructing the bulk of euchromatic genes, with the only limit appearing to be determined by the sequencing depth. For genes imbedded in heterochromatin, however, the low cloning efficiency of repetitive sequences, combined with the computational challenges, demand that additional clues be used to annotate the sequences. One approach that has proven very successful in identifying protein coding genes in Y-linked heterochromatin of Drosophila melanogaster has been to make a BLASTable database of the small, unmapped contigs and fragments leftover at the end of a shotgun assembly, and to attempt to capture these by blasting with an appropriate query sequence. This approach often yields a staggered alignment of contigs from the unmapped set to the query sequence, as though the disjoint contigs represent small portions of the gene. Further inspection frequently shows that the contigs are broken by very large, heterochromatic introns. Methods of this sort are being expanded to make best use of all available clues to determine which unmapped contigs are associated with genes. These include use of EST libraries, and, in the case of the Y chromosome, testing of male specific genes and reduced shotgun depth of relevant contigs. It appears much more hopeful than anyone would have imagined that whole genome shotgun assemblies can recover the great bulk of even heterochromatic genes.