104 research outputs found
Differences in collagen prolyl 4-hydroxylase assembly between two Caenorhabditis nematode species despite high amino acid sequence identity of the enzyme subunits
The collagen prolyl 4-hydroxylases (P4Hs) are
essential for proper extracellular matrix
formation in multicellular organisms. The
vertebrate enzymes are α2β2 tetramers, in
which the β subunits are identical to protein
disulfide isomerase (PDI). Unique P4H forms
have been shown to assemble from the
<i>Caenorhabditis</i> <i>elegans</i> catalytic α subunit
isoforms PHY-1 and PHY-2 and the β subunit
PDI-2. A mixed PHY-1/PHY-2/(PDI-2)<sub>2</sub>
tetramer is the major form, while PHY-1/PDI-
2 and PHY-2/PDI-2 dimers are also assembled
but less efficiently. Cloning and
characterization of the orthologous subunits
from the closely related nematode
<i>Caenorhabditis</i> <i>briggsae</i> revealed distinct
differences in the assembly of active P4H
forms in spite of the extremely high amino
acid sequence identity (92-97%) between the
<i>C. briggsae</i> and <i>C. elegans</i> subunits. In
addition to a PHY-1/PHY-2(PDI-2)<sub>2</sub> tetramer
and a PHY-1/PDI-2 dimer, an active (PHY-
2)<sub>2</sub>(PDI-2)<sub>2</sub> tetramer was formed in <i>C.
briggsae</i> instead of a PHY-2/PDI-2 dimer.
Site-directed mutagenesis studies and
generation of inter-species hybrid polypeptides
showed that the N-terminal halves of the
<i>Caenorhabditis</i> PHY-2 polypeptides
determine their assembly properties. Genetic
disruption of <i>C. briggsae phy-1</i> (<i>Cb-dpy-18</i>)
via a <i>Mos1</i> insertion resulted a small (short)
phenotype that is less severe than the dumpy
(short and fat) phenotype of the corresponding
<i>C. elegans</i> mutants (<i>Ce-dpy-18</i>). <i>C. briggsae</i>
<i>phy-2</i> RNA interference produced no visible
phenotype in the wild type nematodes but
produced a severe dumpy phenotype and larval
arrest in <i>phy-1</i> mutants. Genetic
complementation of the <i>C. briggsae</i> and <i>C.
elegans</i> <i>phy-1</i> mutants was achieved by
injection of a wild type <i>phy-1</i> gene from either
species
Crystal structure of the human, FIC-Domain containing protein HYPE and implications for its functions
Protein AMPylation, the transfer of AMP from ATP to protein targets, has been recognized as a new mechanism of host-cell disruption by some bacterial effectors that typically contain a FIC-domain. Eukaryotic genomes also encode one FIC-domain protein, HYPE, which has remained poorly characterized. Here we describe the structure of human HYPE, solved by X-ray crystallography, representing the first structure of a eukaryotic FIC-domain protein. We demonstrate that HYPE forms stable dimers with structurally and functionally integrated FIC-domains and with TPR-motifs exposed for protein-protein interactions. As HYPE also uniquely possesses a transmembrane helix, dimerization is likely to affect its positioning and function in the membrane vicinity. The low rate of autoAMPylation of the wild-type HYPE could be due to autoinhibition, consistent with the mechanism proposed for a number of putative FIC AMPylators. Our findings also provide a basis to further consider possible alternative cofactors of HYPE and distinct modes of target-recognition
The fitness consequences of inbreeding in natural populations and their implications for species conservation – a systematic map
Background: Threatened species often have small and isolated populations where mating among relatives can
result in inbreeding depression increasing extinction risk. Effective management is hampered by a lack of syntheses
summarising the magnitude of, and variation in inbreeding depression. Here we describe the nature and scope
of the literature examining phenotypic/fitness consequences of inbreeding, to provide a foundation for future
syntheses and management.
Methods: We searched the literature for articles documenting the impact of inbreeding in natural populations.
Article titles, abstracts and full-texts were assessed against a priori defined criteria, and information relating to study
design, quality and other factors that may influence inbreeding responses (e.g. population size) was extracted from
relevant articles.
Results: The searches identified 11457 articles, of which 614 were assessed as relevant and included in the systematic
map (corresponding to 703 distinct studies). Most studies (663) assessed within-population inbreeding resulting from
self-fertilisation or consanguineous pairings, while 118 studies assessed among-population inbreeding due to drift load.
Plants were the most studied taxon (469 studies) followed by insects (52 studies) and birds (43 studies). Most studies
investigated the effects of inbreeding on components of fitness (e.g. survival or fecundity; 648 studies) but measurements
were typically under laboratory/greenhouse conditions (486 studies). Observations were also often restricted to the first
inbred generation (607 studies) and studies frequently lacked contextual information (e.g. population size).
Conclusions: Our systematic map describes the scope and quality of the evidence describing the phenotypic
consequences of inbreeding. The map reveals substantial evidence relating to inbreeding responses exists,
but highlights information is still limited for some aspects, including the effects of multiple generations of
inbreeding. The systematic map allowed us to define several conservation-relevant questions, where sufficient
data exists to support systematic reviews, e.g. How do inbreeding responses vary with population size? However,
we found that such syntheses are likely to be constrained by incomplete reporting of critical contextual information.
Our systematic map employed the same rigorous literature assessment methods as systematic review, including a
novel survey of study quality and thus provides a robust foundation to guide future research and syntheses seeking to
inform conservation decision-making
Packages of Care for Schizophrenia in Low- and Middle-Income Countries
In the third in a series of six articles on packages of care for mental disorders in low- and middle-income countries, Jair Mari and colleagues discuss the treatment of schizophrenia
Accelerated inbreeding depression suggests synergistic epistasis for deleterious mutations in Drosophila melanogaster
Epistasis may have important consequences for a number of issues in quantitative genetics and evolutionary biology. In
particular, synergistic epistasis for deleterious alleles is relevant to the mutation load paradox and the evolution of sex and
recombination. Some studies have shown evidence of synergistic epistasis for spontaneous or induced deleterious mutations
appearing in mutation-accumulation experiments. However, many newly arising mutations may not actually be segregating
in natural populations because of the erasing action of natural selection. A demonstration of synergistic epistasis for naturally
segregating alleles can be achieved by means of inbreeding depression studies, as deleterious recessive allelic effects are
exposed in inbred lines. Nevertheless, evidence of epistasis from these studies is scarce and controversial. In this paper, we
report the results of two independent inbreeding experiments carried out with two different populations of Drosophila
melanogaster. The results show a consistent accelerated inbreeding depression for fitness, suggesting synergistic epistasis
among deleterious alleles. We also performed computer simulations assuming different possible models of epistasis and
mutational parameters for fitness, finding some of them to be compatible with the results observed. Our results suggest that
synergistic epistasis for deleterious mutations not only occurs among newly arisen spontaneous or induced mutations, but
also among segregating alleles in natural populationsWe acknowledge the support by Uvigo
Marine Research Centre funded by the “Excellence in Research
(INUGA)” Programme from the Regional Council of Culture, Education and Universities, with co-funding from the European Union
through the ERDF Operational Programme Galicia 2014-2020. This
work was funded by Agencia Estatal de Investigación (AEI) (CGL2016-75904-C2-1-P), Xunta de Galicia (ED431C 2016-037) and
Fondos Feder: “Unha maneira de facer Europa.” SD was founded by a
predoctoral (FPI) grant from Ministerio de Economía y
Competitividad, SpainS
Predicting probable Alzheimer's disease using linguistic deficits and biomarkers
BackgroundThe manual diagnosis of neurodegenerative disorders such as Alzheimer’s disease (AD) and related Dementias has been a challenge. Currently, these disorders are diagnosed using specific clinical diagnostic criteria and neuropsychological examinations. The use of several Machine Learning algorithms to build automated diagnostic models using low-level linguistic features resulting from verbal utterances could aid diagnosis of patients with probable AD from a large population. For this purpose, we developed different Machine Learning models on the DementiaBank language transcript clinical dataset, consisting of 99 patients with probable AD and 99 healthy controls.ResultsOur models learned several syntactic, lexical, and n-gram linguistic biomarkers to distinguish the probable AD group from the healthy group. In contrast to the healthy group, we found that the probable AD patients had significantly less usage of syntactic components and significantly higher usage of lexical components in their language. Also, we observed a significant difference in the use of n-grams as the healthy group were able to identify and make sense of more objects in their n-grams than the probable AD group. As such, our best diagnostic model significantly distinguished the probable AD group from the healthy elderly group with a better Area Under the Receiving Operating Characteristics Curve (AUC) using the Support Vector Machines (SVM).ConclusionsExperimental and statistical evaluations suggest that using ML algorithms for learning linguistic biomarkers from the verbal utterances of elderly individuals could help the clinical diagnosis of probable AD. We emphasise that the best ML model for predicting the disease group combines significant syntactic, lexical and top n-gram features. However, there is a need to train the diagnostic models on larger datasets, which could lead to a better AUC and clinical diagnosis of probable AD
- …