Anaerobic oxidation of methane associated with sulfate reduction in a natural freshwater gas source

The occurrence of anaerobic oxidation of methane (AOM) and trace methane oxidation (TMO) was investigated in a freshwater natural gas source. Sediment samples were taken and analyzed for potential electron acceptors coupled to AOM. Long-term incubations with 13C-labeled CH4 (13CH4) and different electron acceptors showed that both AOM and TMO occurred. In most conditions, 13C-labeled CO2 (13CO2) simultaneously increased with methane formation, which is typical for TMO. In the presence of nitrate, neither methane formation nor methane oxidation occurred. Net AOM was measured only with sulfate as electron acceptor. Here, sulfide production occurred simultaneously with 13CO2 production and no methanogenesis occurred, excluding TMO as a possible source for 13CO2 production from 13CH4. Archaeal 16S rRNA gene analysis showed the highest presence of ANME-2a/b (ANaerobic MEthane oxidizing archaea) and AAA (AOM Associated Archaea) sequences in the incubations with methane and sulfate as compared with only methane addition. Higher abundance of ANME-2a/b in incubations with methane and sulfate as compared with only sulfate addition was shown by qPCR analysis. Bacterial 16S rRNA gene analysis showed the presence of sulfate-reducing bacteria belonging to SEEP-SRB1. This is the first report that explicitly shows that AOM is associated with sulfate reduction in an enrichment culture of ANME-2a/b and AAA methanotrophs and SEEP-SRB1 sulfate reducers from a low-saline environment.We thank Douwe Bartstra (Vereniging tot Behoud van de Gasbronnen in Noord-Holland, The Netherlands), Carla Frijters (Paques BV, The Netherlands) and Teun Veuskens (Laboratory of Microbiology, WUR, The Netherlands) for sampling; Martin Meirink (Hoogheemraadschap Hollands Noorderkwartier, The Netherlands) for physicochemical data; Freek van Sambeek for providing Figure 1; Lennart Kleinjans (Laboratory of Microbiology, WUR, The Netherlands) for help with pyrosequencing analysis, Irene Sánchez-Andrea (Laboratory of Microbiology, WUR, The Netherlands) for proof-reading and Katharina Ettwig (Department of Microbiology, Radboud University Nijmegen, The Netherlands) for providing M. oxyfera DNA. We want to thank all anonymous reviewers for valuable contributions. This research is supported by the Dutch Technology Foundation STW (project 10711), which is part of the Netherlands Organization for Scientific Research (NWO), and which is partly funded by the Ministry of Economic Affairs. Research of AJMS is supported by ERC grant (project 323009) and the Gravitation grant (project 024.002.002) of the Netherlands Ministry of Education, Culture and Science and the Netherlands Science Foundation (NWO)

Oxidative stress and proinflammatory cytokines contribute to demyelination and axonal damage in a cerebellar culture model of neuroinflammation

Background: Demyelination and axonal damage are critical processes in the pathogenesis of multiple sclerosis (MS). Oxidative stress and pro-inflammatory cytokines elicited by inflammation mediates tissue damage. Methods/Principal Findings: To monitor the demyelination and axonal injury associated with microglia activation we employed a model using cerebellar organotypic cultures stimulated with lipopolysaccharide (LPS). Microglia activated by LPS released pro-inflammatory cytokines (IL-1β, IL-6 and TNFα), and increased the expression of inducible nitric oxide synthase (iNOS) and production of reactive oxygen species (ROS). This activation was associated with demyelination and axonal damage in cerebellar cultures. Axonal damage, as revealed by the presence of non-phosphorylated neurofilaments, mitochondrial accumulation in axonal spheroids, and axonal transection, was associated with stronger iNOS expression and concomitant increases in ROS. Moreover, we analyzed the contribution of pro-inflammatory cytokines and oxidative stress in demyelination and axonal degeneration using the iNOS inhibitor ethyl pyruvate, a free-scavenger and xanthine oxidase inhibitor allopurinol, as well as via blockage of pro-inflammatory cytokines using a Fc-TNFR1 construct. We found that blocking microglia activation with ethyl pyruvate or allopurinol significantly decreased axonal damage, and to a lesser extent, demyelination. Blocking TNFα significantly decreased demyelination but did not prevented axonal damage. Moreover, the most common therapy for MS, interferon-beta, was used as an example of an immunomodulator compound that can be tested in this model. In vitro, interferon-beta treatment decreased oxidative stress (iNOS and ROS levels) and the release of pro-inflammatory cytokines after LPS stimulation, reducing axonal damage. Conclusion: The model of neuroinflammation using cerebellar culture stimulated with endotoxin mimicked myelin and axonal damage mediated by the combination of oxidative stress and pro-inflammatory cytokines. This model may both facilitate understanding of the events involved in neuroinflammation and aid in the development of neuroprotective therapies for the treatment of MS and other neurodegenerative diseases

Inferring transcriptional compensation interactions in yeast via stepwise structure equation modeling

<p>Abstract</p> <p>Background</p> <p>With the abundant information produced by microarray technology, various approaches have been proposed to infer transcriptional regulatory networks. However, few approaches have studied subtle and indirect interaction such as genetic compensation, the existence of which is widely recognized although its mechanism has yet to be clarified. Furthermore, when inferring gene networks most models include only observed variables whereas latent factors, such as proteins and mRNA degradation that are not measured by microarrays, do participate in networks in reality.</p> <p>Results</p> <p>Motivated by inferring transcriptional compensation (TC) interactions in yeast, a stepwise structural equation modeling algorithm (SSEM) is developed. In addition to observed variables, SSEM also incorporates hidden variables to capture interactions (or regulations) from latent factors. Simulated gene networks are used to determine with which of six possible model selection criteria (MSC) SSEM works best. SSEM with Bayesian information criterion (BIC) results in the highest true positive rates, the largest percentage of correctly predicted interactions from all existing interactions, and the highest true negative (non-existing interactions) rates. Next, we apply SSEM using real microarray data to infer TC interactions among (1) small groups of genes that are synthetic sick or lethal (SSL) to SGS1, and (2) a group of SSL pairs of 51 yeast genes involved in DNA synthesis and repair that are of interest. For (1), SSEM with BIC is shown to outperform three Bayesian network algorithms and a multivariate autoregressive model, checked against the results of qRT-PCR experiments. The predictions for (2) are shown to coincide with several known pathways of Sgs1 and its partners that are involved in DNA replication, recombination and repair. In addition, experimentally testable interactions of Rad27 are predicted.</p> <p>Conclusion</p> <p>SSEM is a useful tool for inferring genetic networks, and the results reinforce the possibility of predicting pathways of protein complexes via genetic interactions.</p

Estrogen protects neuronal cells from amyloid beta-induced apoptosis via regulation of mitochondrial proteins and function

BACKGROUND: Neurodegeneration in Alzheimer's disease is associated with increased apoptosis and parallels increased levels of amyloid beta, which can induce neuronal apoptosis. Estrogen exposure prior to neurotoxic insult of hippocampal neurons promotes neuronal defence and survival against neurodegenerative insults including amyloid beta. Although all underlying molecular mechanisms of amyloid beta neurotoxicity remain undetermined, mitochondrial dysfunction, including altered calcium homeostasis and Bcl-2 expression, are involved in neurodegenerative vulnerability. RESULTS: In this study, we investigated the mechanism of 17β-estradiol-induced prevention of amyloid beta-induced apoptosis of rat hippocampal neuronal cultures. Estradiol treatment prior to amyloid beta exposure significantly reduced the number of apoptotic neurons and the associated rise in resting intracellular calcium levels. Amyloid beta exposure provoked down regulation of a key antiapoptotic protein, Bcl-2, and resulted in mitochondrial translocation of Bax, a protein known to promote cell death, and subsequent release of cytochrome c. E(2 )pretreatment inhibited the amyloid beta-induced decrease in Bcl-2 expression, translocation of Bax to the mitochondria and subsequent release of cytochrome c. Further implicating the mitochondria as a target of estradiol action, in vivo estradiol treatment enhanced the respiratory function of whole brain mitochondria. In addition, estradiol pretreatment protected isolated mitochondria against calcium-induced loss of respiratory function. CONCLUSION: Therefore, we propose that estradiol pretreatment protects against amyloid beta neurotoxicity by limiting mitochondrial dysfunction via activation of antiapoptotic mechanisms

Selective inhibition of the human tie-1 promoter with triplex-forming oligonucleotides targeted to ets binding sites

The Tie receptors (Tie-1 and Tie-2/Tek) are essential for angiogenesis and vascular remodeling/integrity. Tie receptors are up-regulated in tumor-associated endothelium, and their inhibition disrupts angiogenesis and can prevent tumor growth as a consequence. To investigate the potential of anti-gene approaches to inhibit tie gene expression for anti-angiogenic therapy, we have examined triple-helical (triplex) DNA formation at 2 tandem Ets transcription factor binding motifs (designated E-1 and E-2) in the human tie-1 promoter. Various tie-1 promoter deletion/mutation luciferase reporter constructs were generated and transfected into endothelial cells to examine the relative activities of E-1 and E-2. The binding of antiparallel and parallel (control) purine motif oligonucleotides (21-22 bp) targeted to E-1 and E-2 was assessed by plasmid DNA fragment binding and electrophoretic mobility shift assays. Triplex-forming oligonucleotides were incubated with tie-1 reporter constructs and transfected into endothelial cells to determine their activity. The Ets binding motifs in the E-1 sequence were essential for human tie-1 promoter activity in endothelial cells, whereas the deletion of E-2 had no effect. Antiparallel purine motif oligonucleotides targeted at E-1 or E-2 selectively formed strong triplex DNA (K(d) approximately 10(-7) M) at 37 degrees C. Transfection of tie-1 reporter constructs with triplex DNA at E-1, but not E-2, specifically inhibited tie-1 promoter activity by up to 75% compared with control oligonucleotides in endothelial cells. As similar multiple Ets binding sites are important for the regulation of several endothelial-restricted genes, this approach may have broad therapeutic potential for cancer and other pathologies involving endothelial proliferation/dysfunction

A call for transparent reporting to optimize the predictive value of preclinical research

The US National Institute of Neurological Disorders and Stroke convened major stakeholders in June 2012 to discuss how to improve the methodological reporting of animal studies in grant applications and publications. The main workshop recommendation is that at a minimum studies should report on sample-size estimation, whether and how animals were randomized, whether investigators were blind to the treatment, and the handling of data. We recognize that achieving a meaningful improvement in the quality of reporting will require a concerted effort by investigators, reviewers, funding agencies and journal editors. Requiring better reporting of animal studies will raise awareness of the importance of rigorous study design to accelerate scientific progress

Genomic reconstruction of the SARS-CoV-2 epidemic in England.

The evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus leads to new variants that warrant timely epidemiological characterization. Here we use the dense genomic surveillance data generated by the COVID-19 Genomics UK Consortium to reconstruct the dynamics of 71 different lineages in each of 315 English local authorities between September 2020 and June 2021. This analysis reveals a series of subepidemics that peaked in early autumn 2020, followed by a jump in transmissibility of the B.1.1.7/Alpha lineage. The Alpha variant grew when other lineages declined during the second national lockdown and regionally tiered restrictions between November and December 2020. A third more stringent national lockdown suppressed the Alpha variant and eliminated nearly all other lineages in early 2021. Yet a series of variants (most of which contained the spike E484K mutation) defied these trends and persisted at moderately increasing proportions. However, by accounting for sustained introductions, we found that the transmissibility of these variants is unlikely to have exceeded the transmissibility of the Alpha variant. Finally, B.1.617.2/Delta was repeatedly introduced in England and grew rapidly in early summer 2021, constituting approximately 98% of sampled SARS-CoV-2 genomes on 26 June 2021

The back-step method—Method for obtaining unbiased population parameter estimates for ordered categorical data

A significant bias in parameters, estimated with the proportional odds model using the software NONMEM, has been reported. Typically, this bias occurs with ordered categorical data, when most of the observations are found at one extreme of the possible outcomes. The aim of this study was to assess, through simulations, the performance of the Back-Step Method (BSM), a novel approach for obtaining unbiased estimates when the standard approach provides biased estimates. BSM is an iterative method involving sequential simulation-estimation steps. BSM was compared with the standard approach in the analysis of a 4-category ordered variable using the Laplacian method in NONMEM. The bias in parameter estimates and the accuracy of model predictions were determined for the 2 methods on 3 conditions: (1) a nonskewed distribution of the response with low interindividual variability (IIV), (2) a skewed distribution with low IIV, and (3) a skewed distribution with high IIV. An increase in bias with increasing skewness and IIV was shown in parameters estimated using the standard approach in NON-MEM. BSM performed without appreciable bias in the estimates under the 3 conditions, and the model predictions were in good agreement with the original data. Each BSM estimation represents a random sample of the population; hence, repeating the BSM estimation reduces the imprecision of the parameter estimates. The BSM is an accurate estimation method when the standard modeling approach in NONMEM gives biased estimates