716 research outputs found
Complementation of diverse HIV-1 Env defects through cooperative subunit interactions: a general property of the functional trimer
<p>Abstract</p> <p>Background</p> <p>The HIV-1 Env glycoprotein mediates virus entry by catalyzing direct fusion between the virion membrane and the target cell plasma membrane. Env is composed of two subunits: gp120, which binds to CD4 and the coreceptor, and gp41, which is triggered upon coreceptor binding to promote the membrane fusion reaction. Env on the surface of infected cells is a trimer consisting of three gp120/gp41 homo-dimeric protomers. An emerging question concerns cooperative interactions between the protomers in the trimer, and possible implications for Env function.</p> <p>Results</p> <p>We extended studies on cooperative subunit interactions within the HIV-1 Env trimer, using analysis of functional complementation between coexpressed inactive variants harboring different functional deficiencies. In assays of Env-mediated cell fusion, complementation was observed between variants with a wide range of defects in both the gp120 and gp41 subunits. The former included gp120 subunits mutated in the CD4 binding site or incapable of coreceptor interaction due either to mismatched specificity or V3 loop mutation. Defective gp41 variants included point mutations at different residues within the fusion peptide or heptad repeat regions, as well as constructs with modifications or deletions of the membrane proximal tryptophan-rich region or the transmembrane domain. Complementation required the defective variants to be coexpressed in the same cell. The observed complementation activities were highly dependent on the assay system. The most robust activities were obtained with a vaccinia virus-based expression and reporter gene activation assay for cell fusion. In an alternative system involving Env expression from integrated provirus, complementation was detected in cell fusion assays, but not in virus particle entry assays.</p> <p>Conclusion</p> <p>Our results indicate that Env function does not require every subunit in the trimer to be competent for all essential activities. Through cross-talk between subunits, the functional determinants on one defective protomer can cooperatively interact to trigger the functional determinants on an adjacent protomer(s) harboring a different defect, leading to fusion. Cooperative subunit interaction is a general feature of the Env trimer, based on complementation activities observed for a highly diverse range of functional defects.</p
Gut microbiome and brain functional connectivity in infants-a preliminary study focusing on the amygdala
Recently, there has been a surge of interest in the possibility that microbial communities inhabiting the human gut could affect cognitive development and increase risk for mental illness via the “microbiome-gut-brain axis.” Infancy likely represents a critical period for the establishment of these relationships, as it is the most dynamic stage of postnatal brain development and a key period in the maturation of the microbiome. Indeed, recent reports indicate that characteristics of the infant gut microbiome are associated with both temperament and cognitive performance. The neural circuits underlying these relationships have not yet been delineated. To address this gap, resting-state fMRI scans were acquired from 39 1-year-old human infants who had provided fecal samples for identification and relative quantification of bacterial taxa. Measures of alpha diversity were generated and tested for associations with measures of functional connectivity. Primary analyses focused on the amygdala as manipulation of the gut microbiota in animal models alters the structure and neurochemistry of this brain region. Secondary analyses explored functional connectivity of nine canonical resting-state functional networks. Alpha diversity was significantly associated with functional connectivity between the amygdala and thalamus and between the anterior cingulate cortex and anterior insula. These regions play an important role in processing/responding to threat. Alpha diversity was also associated with functional connectivity between the supplementary motor area (SMA, representing the sensorimotor network) and the inferior parietal lobule (IPL). Importantly, SMA-IPL connectivity also related to cognitive outcomes at 2 years of age, suggesting a potential pathway linking gut microbiome diversity and cognitive outcomes during infancy. These results provide exciting new insights into the gut-brain axis during early human development and should stimulate further studies into whether microbiome-associated changes in brain circuitry influence later risk for psychopathology
Resting state network topology of the ferret brain
Resting state functional magnetic resonance imaging (rsfMRI) has emerged as a versatile tool for non-invasive measurement of functional connectivity patterns in the brain. RsfMRI brain dynamics in rodents, non-human primates, and humans share similar properties; however, little is known about the resting state functional connectivity patterns in the ferret, an animal model with high potential for developmental and cognitive translational study. To address this knowledge-gap, we performed rsfMRI on anesthetized ferrets using a 9.4 tesla MRI scanner, and subsequently performed group-level independent component analysis (gICA) to identify functionally connected brain networks. Group-level ICA analysis revealed distributed sensory, motor, and higher-order networks in the ferret brain. Subsequent connectivity analysis showed interconnected higher-order networks that constituted a putative default mode network (DMN), a network that exhibits altered connectivity in neuropsychiatric disorders. Finally, we assessed ferret brain topological efficiency using graph theory analysis and found that the ferret brain exhibits small-world properties. Overall, these results provide additional evidence for pan-species resting-state networks, further supporting ferret-based studies of sensory and cognitive function
Prenatal Drug Exposure Affects Neonatal Brain Functional Connectivity
Prenatal drug exposure, particularly prenatal cocaine exposure (PCE), incurs great public and scientific interest because of its associated neurodevelopmental consequences. However, the neural underpinnings of PCE remain essentially uncharted, and existing studies in school-aged children and adolescents are confounded greatly by postnatal environmental factors. In this study, leveraging a large neonate sample (N = 152) and non-invasive resting-state functional magnetic resonance imaging, we compared human infants with PCE comorbid with other drugs (such as nicotine, alcohol, marijuana, and antidepressant) with infants with similar non-cocaine poly drug exposure and drug-free controls. We aimed to characterize the neural correlates of PCE based on functional connectivity measurements of the amygdala and insula at the earliest stage of development. Our results revealed common drug exposure-related connectivity disruptions within the amygdala–frontal, insula–frontal, and insula–sensorimotor circuits. Moreover, a cocaine-specific effect was detected within a subregion of the amygdala–frontal network. This pathway is thought to play an important role in arousal regulation, which has been shown to be irregular in PCE infants and adolescents. These novel results provide the earliest human-based functional delineations of the neural-developmental consequences of prenatal drug exposure and thus open a new window for the advancement of effective strategies aimed at early risk identification and intervention
The UNC/UMN Baby Connectome Project (BCP): An overview of the study design and protocol development
The human brain undergoes extensive and dynamic growth during the first years of life. The UNC/UMN Baby Connectome Project (BCP), one of the Lifespan Connectome Projects funded by NIH, is an ongoing study jointly conducted by investigators at the University of North Carolina at Chapel Hill and the University of Minnesota. The primary objective of the BCP is to characterize brain and behavioral development in typically developing infants across the first 5 years of life. The ultimate goals are to chart emerging patterns of structural and functional connectivity during this period, map brain-behavior associations, and establish a foundation from which to further explore trajectories of health and disease. To accomplish these goals, we are combining state of the art MRI acquisition and analysis techniques, including high-resolution structural MRI (T1-and T2-weighted images), diffusion imaging (dMRI), and resting state functional connectivity MRI (rfMRI). While the overall design of the BCP largely is built on the protocol developed by the Lifespan Human Connectome Project (HCP), given the unique age range of the BCP cohort, additional optimization of imaging parameters and consideration of an age appropriate battery of behavioral assessments were needed. Here we provide the overall study protocol, including approaches for subject recruitment, strategies for imaging typically developing children 0–5 years of age without sedation, imaging protocol and optimization, a description of the battery of behavioral assessments, and QA/QC procedures. Combining HCP inspired neuroimaging data with well-established behavioral assessments during this time period will yield an invaluable resource for the scientific community
Time-resolved single-particle x-ray scattering reveals electron-density as coherent plasmonic-nanoparticle-oscillation source
Dynamics of optically-excited plasmonic nanoparticles are presently
understood as a series of sequential scattering events, involving
thermalization processes after pulsed optical excitation. One important step is
the initiation of nanoparticle breathing oscillations. According to established
experiments and models, these are caused by the statistical heat transfer from
thermalized electrons to the lattice. An additional contribution by hot
electron pressure has to be included to account for phase mismatches that arise
from the lack of experimental data on the breathing onset. We used optical
transient-absorption spectroscopy and time-resolved single-particle
x-ray-diffractive imaging to access the excited electron system and lattice.
The time-resolved single-particle imaging data provided structural information
directly on the onset of the breathing oscillation and confirmed the need for
an additional excitation mechanism to thermal expansion, while the observed
phase-dependence of the combined structural and optical data contrasted
previous studies. Therefore, we developed a new model that reproduces all our
experimental observations without using fit parameters. We identified
optically-induced electron density gradients as the main driving source.Comment: 32 pages, 5 figures, 1 supporting information document include
Polymorphisms in Gag spacer peptide 1 confer varying levels of resistance to the HIV- 1maturation inhibitor bevirimat
Background: The maturation inhibitor bevirimat (BVM) potently inhibits human immunodeficiency virus type 1 (HIV-1) replication by blocking capsid-spacer peptide 1 (CA-SP1) cleavage. Recent clinical trials demonstrated that a significant proportion of HIV-1-infected patients do not respond to BVM. A patient’s failure to respond correlated with baseline polymorphisms at SP1 residues 6-8. Results: In this study, we demonstrate that varying levels of BVM resistance are associated with point mutations at these residues. BVM susceptibility was maintained by SP1-Q6A, -Q6H and -T8A mutations. However, an SP1-V7A mutation conferred high-level BVM resistance and SP1-V7M and T8Δ mutations conferred intermediate levels of BVM resistance. Conclusions: Future exploitation of the CA-SP1 cleavage site as an antiretroviral drug target will need to overcome the baseline variability in the SP1 region of Gag.Publisher PDFPeer reviewe
Subtidal macrozoobenthos communities from northern Chile during and post El Niño 1997–1998
Despite a large amount of climatic and oceanographic information dealing with the recurring climate phenomenon El Niño (EN) and its well known impact on diversity of marine benthic communities, most published data are rather descriptive and consequently our understanding of the underlying mechanisms and processes that drive community structure during EN are still very scarce. In this study, we address two questions on the effects of EN on macrozoobenthic communities: (1) how does EN affect species diversity of the communities in northern Chile? and (2) is EN a phenomenon that restarts community assembling processes by affecting species interactions in northern Chile? To answer these questions, we compared species diversity and co-occurrence patterns of soft-bottoms macrozoobenthos communities from the continental shelf off northern Chile during (March 1998) and after (September 1998) the strong EN event 1997–1998. The methods used varied from species diversity and species co-occurrence analyses to multivariate ordination methods.
Our results indicate that EN positively affects diversity of macrozoobenthos communities in the study area, increasing the species richness and diversity and decreasing the species dominance. EN represents a strong disturbance that affects species interactions that rule the species assembling processes in shallow-water, sea-bottom environments
Predicting Bevirimat resistance of HIV-1 from genotype
<p>Abstract</p> <p>Background</p> <p>Maturation inhibitors are a new class of antiretroviral drugs. Bevirimat (BVM) was the first substance in this class of inhibitors entering clinical trials. While the inhibitory function of BVM is well established, the molecular mechanisms of action and resistance are not well understood. It is known that mutations in the regions CS p24/p2 and p2 can cause phenotypic resistance to BVM. We have investigated a set of p24/p2 sequences of HIV-1 of known phenotypic resistance to BVM to test whether BVM resistance can be predicted from sequence, and to identify possible molecular mechanisms of BVM resistance in HIV-1.</p> <p>Results</p> <p>We used artificial neural networks and random forests with different descriptors for the prediction of BVM resistance. Random forests with hydrophobicity as descriptor performed best and classified the sequences with an area under the Receiver Operating Characteristics (ROC) curve of 0.93 ± 0.001. For the collected data we find that p2 sequence positions 369 to 376 have the highest impact on resistance, with positions 370 and 372 being particularly important. These findings are in partial agreement with other recent studies. Apart from the complex machine learning models we derived a number of simple rules that predict BVM resistance from sequence with surprising accuracy. According to computational predictions based on the data set used, cleavage sites are usually not shifted by resistance mutations. However, we found that resistance mutations could shorten and weaken the <it>α</it>-helix in p2, which hints at a possible resistance mechanism.</p> <p>Conclusions</p> <p>We found that BVM resistance of HIV-1 can be predicted well from the sequence of the p2 peptide, which may prove useful for personalized therapy if maturation inhibitors reach clinical practice. Results of secondary structure analysis are compatible with a possible route to BVM resistance in which mutations weaken a six-helix bundle discovered in recent experiments, and thus ease Gag cleavage by the retroviral protease.</p
Transverse sphericity of primary charged particles in minimum bias proton-proton collisions at , 2.76 and 7 TeV
Measurements of the sphericity of primary charged particles in minimum bias
proton--proton collisions at , 2.76 and 7 TeV with the ALICE
detector at the LHC are presented. The observable is linearized to be collinear
safe and is measured in the plane perpendicular to the beam direction using
primary charged tracks with GeV/c in . The
mean sphericity as a function of the charged particle multiplicity at
mid-rapidity () is reported for events with different
scales ("soft" and "hard") defined by the transverse momentum of the leading
particle. In addition, the mean charged particle transverse momentum versus
multiplicity is presented for the different event classes, and the sphericity
distributions in bins of multiplicity are presented. The data are compared with
calculations of standard Monte Carlo event generators. The transverse
sphericity is found to grow with multiplicity at all collision energies, with a
steeper rise at low , whereas the event generators show the
opposite tendency. The combined study of the sphericity and the mean with multiplicity indicates that most of the tested event generators
produce events with higher multiplicity by generating more back-to-back jets
resulting in decreased sphericity (and isotropy). The PYTHIA6 generator with
tune PERUGIA-2011 exhibits a noticeable improvement in describing the data,
compared to the other tested generators.Comment: 21 pages, 9 captioned figures, 3 tables, authors from page 16,
published version, figures from
http://aliceinfo.cern.ch/ArtSubmission/node/308
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