Variability Of Biological Processes Research Articles

A Method for Comparing Time Series by Untangling Time-Dependent and Independent Variations in Biological Processes

Biological processes like growth, aging, and disease progression are generally studied with follow-up scans taken at different time points, i.e., image time series (TS) based analysis. Image TS represents the evolution of anatomy over time, but different anatomies may have different structural characteristics and temporal paths. Therefore, separating the time-dependent path difference and time-independent basic anatomy/shape changes is important when comparing two image TS to understand the causes of the observed differences better. A method to untangle and quantify the path and shape difference between the TS is presented in this paper. The proposed method is evaluated with simulated and adult and fetal neuro templates. Results show that the metric can separate and quantify the path and shape differences between TS.

AAV8-P301L tau expression confers age-related disruptions in sleep quantity and timing

Sleep timing and quantity disturbances persist in tauopathy patients. This has been studied in transgenic models of primary tau neuropathology using traditional electroencephalograms (EEGs) and more recently, the PiezoSleep Mouse Behavioral Tracking System. Here, we generated a primary tauopathy model using an intracerebroventricular injection of human mutant hSyn-P301L-tau, using adeno-associated virus of serotype 8 (AAV8). We discovered distinctions in sleep architecture with altered quantity and timing in AAV8-P301L tau expressing mice of both sexes using the noninvasive PiezoSleep System. The AAV8-P301L tau mice exhibit striking age-related increases in sleep duration specifically at the active phase onset, suggesting a critical and sensitive time-of-day for tauopathy related sleep disturbances to occur. Since our findings show sleep behavior changes at specific transitional periods of the day, tau neuropathology may impact normal diurnal variation in biological processes, which should be explored using the AAV8-P301L tauopathy model.

191 Awardee Talk: Characterizing biological processes influencing the efficiency of nutrient utilization in growing cattle

Abstract 2Abstract: Residual feed intake (RFI), a metric of feed efficiency, is moderately heritable and minimally associated with body size and productivity, making it an ideal trait for investigation as a selection criterion to improve feed efficiency of growing cattle. The objective of this research was to characterize the inter-animal variation in biological processes of growing cattle selected to be divergent in RFI. Holstein heifers [n = 55; body weight (BW) = 351 ± 64 kg) with low- (n = 29) or high- (n = 26) genomically enhanced RFI (RFIg) were selected from a contemporary group of 453 heifers. Heifers were assigned to 1 of 2 pens, equipped with electronic feed bunks and a GreenFeed gaseous-exchange measurement system. Individual dry matter intake (DMI) and feeding behavior data were collected for 84-d. Body weight was measured weekly, and spot fecal samples collected at weighing. Phenotypic RFI (RFIp) was calculated as the residual from regression of DMI on ADG and mid-test BW0.75. On d 70 of the study a rumen fluid sample was collected via esophageal tubing. Blood samples were collected and analyzed for complete blood count (CBC). A mixed model including the fixed effect of RFIg classification and random effect of pen was used to evaluate the effect of RFIg classification on response variables. There were no differences (P > 0.05) in BW and ADG for heifers with divergent RFIg; however, low RFIg heifers consumed 7.5% less (P < 0.05) feed per day. Consequently, low RFIg heifers exhibited a more favorable (P < 0.05) RFIp (-0.188 vs 0.211 kg/d, respectively). Low RFIg heifers exhibited more favorable feeding behavior, with 8.7% fewer (P < 0.05) bunk visit events per day and an 11.2% slower (P ≤ 0.05) eating rate. Low RFIg heifers had 12.5% greater (P < 0.05) total rumen volatile fatty acid concentrations than high RFIg heifers, indicating potentially enhanced microbial fermentation and improved efficiency of feed utilization. Low RFIg heifers had 8.2% less (P < 0.05) methane emissions (g/d), 6.3% less (P < 0.05) carbon dioxide production (g/d), and 6.1% less (P < 0.05) heat production (Mcal/d) calculated according to Brouwer (1965) than high RFIg heifers. Dry matter digestibility did not differ (P > 0.05) between heifers with divergent RFIg. Overall, heifers selected to be more feed efficient exhibited more favorable energy efficiencies and feed efficiency phenotypes. To quantify the variation in RFIg explained by feeding behavior, gas flux, digestibility and rumen fermentation, and CBC partial least squares regression models were developed. Feeding behavior accounted for the largest proportion of variation in RFIg (28.8%). Upon sequential addition of gas flux, digestibility and rumen fermentation, and CBC to feeding behavior, 56.3% of the variation in RFIg was accounted for. Identifying the magnitude at which metabolic processes influence inter-animal variation in efficiency of nutrient utilization provides opportunities to discover valuable candidate biomarkers for selection of more feed efficient cattle.

Using clusterProfiler to characterize multiomics data.

With the advent of multiomics, software capable of multidimensional enrichment analysis has become increasingly crucial for uncovering gene set variations in biological processes and disease pathways. This is essential for elucidating disease mechanisms and identifying potential therapeutic targets. clusterProfiler stands out for its comprehensive utilization of databases and advanced visualization features. Importantly, clusterProfiler supports various biological knowledge, including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, through performing over-representation and gene set enrichment analyses. A key feature is that clusterProfiler allows users to choose from various graphical outputs to visualize results, enhancing interpretability. This protocol describes innovative ways in which clusterProfiler has been used for integrating metabolomics and metagenomics analyses, identifying and characterizing transcription factors under stress conditions, and annotating cells in single-cell studies. In all cases, the computational steps can be completed within ~2 min. clusterProfiler is released through the Bioconductor project and can be accessed via https://bioconductor.org/packages/clusterProfiler/ .

Gamma-band entrainment abnormalities in schizophrenia: Modality-specific or cortex-wide impairment?

A growing body of literature suggests that cognitive impairment in people with schizophrenia (PSZ) results from disrupted cortical excitatory/inhibitory (E-I) balance, which may be linked to gamma entrainment and can be measured noninvasively using electroencephalography (EEG). However, it is not yet known the degree to which these entrainment abnormalities covary within subjects across sensory modalities. Furthermore, the degree to which cross-modal gamma entrainment reflects variation in biological processes associated with cognitive performance remains unclear. We used EEG to measure entrainment to repetitive auditory and visual stimulation at beta (20 Hz) and gamma (30 and 40 Hz) frequencies in PSZ (n = 78) and healthy control subjects (HCS; n = 80). Three indices were measured for each frequency and modality: event-related spectral perturbation (ERSP), intertrial coherence (ITC), and phase-lag angle (PLA). Cognition and symptom severity were also assessed. We found little evidence that gamma entrainment covaried across sensory modalities. PSZ exhibited a modest correlation between modalities at 40 Hz for ERSP and ITC measures (r = 0.23-0.24); however, no other significant correlations between modalities emerged for either HCS or PSZ. Both univariate and multivariate analyses revealed that (a) the pattern of entrainment abnormalities in PSZ differed across modalities, and (b) modality rather than frequency band was the main source of variance. Finally, we observed a significant association between cognition and gamma entrainment in the auditory domain only in HCS. Gamma-band EEG entrainment does not reflect a unitary transcortical mechanism but is instead modality specific. To the extent that entrainment reflects the integrity of cortical E-I balance, the deficits observed in PSZ appear to be modality specific and not consistently associated with cognitive impairment. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Identification of a lncRNA based signature for pancreatic cancer survival to predict immune landscape and potential therapeutic drugs.

Pancreatic cancer is one major digestive malignancy with a poor prognosis. Given the clinical importance of lncRNAs, developing a novel molecular panel with lncRNAs for pancreatic cancer has great potential. As a result, an 8-lncRNA-based robust prognostic signature was constructed using a random survival forest model after examing the expression profile and prognostic significance of lncRNAs in the PAAD cohort from TCGA. The efficacy and effectiveness of the lncRNA-based signature were thoroughly assessed. Patients with high- and low-risk defined by the signature underwent significantly distinct OS expectancy. Most crucially the training group’s AUCs of ROC approached 0.90 and the testing group similarly had the AUCs above 0.86. The lncRNA-based signature was shown to behave as a prognostic indicator of pancreatic cancer, either alone or simultaneously with other factors, after combined analysis with other clinical-pathological factors in Cox regression and nomogram. Additionally, using GSEA and CIBERSORT scoring methods, the immune landscape and variations in biological processes between high- and low-risk subgroups were investigated. Last but not least, drug databases were searched for prospective therapeutic molecules targeting high-risk patients. The most promising compound were Afatinib, LY-303511, and RO-90-7501 as a result. In conclusion, we developed a novel lncRNA based prognostic signature with high efficacy to stratify high-risk pancreatic cancer patients and screened prospective responsive drugs for targeting strategy.

Understanding the Role of Autophagy in Cancer Formation and Progression Is a Real Opportunity to Treat and Cure Human Cancers.

Simple SummaryThe modulation of autophagy represents a potential therapeutic strategy for cancer. More than one hundred clinical trials have been conducted or are ongoing to explore the efficacy of autophagy modulators to reduce the tumor growth and potentiate the anti-cancer effects of conventional therapy. Despite this, the effective role of autophagy during tumor initiation, growth, and metastasis remains not well understood. Depending on the cancer type and stage of cancer, autophagy may have tumor suppressor properties as well as help cancer cells to proliferate and evade cancer therapy. The current review aims to summarize the current knowledge about the autophagy implications in cancer and report the therapeutic opportunities based on the modulation of the autophagy process.The malignant transformation of a cell produces the accumulation of several cellular adaptions. These changes determine variations in biological processes that are necessary for a cancerous cell to survive during stressful conditions. Autophagy is the main nutrient recycling and metabolic adaptor mechanism in eukaryotic cells, represents a continuous source of energy and biomolecules, and is fundamental to preserve the correct cellular homeostasis during unfavorable conditions. In recent decades, several findings demonstrate a close relationship between autophagy, malignant transformation, and cancer progression. The evidence suggests that autophagy in the cancer context has a bipolar role (it may act as a tumor suppressor and as a mechanism of cell survival for established tumors) and demonstrates that the targeting of autophagy may represent novel therapeutic opportunities. Accordingly, the modulation of autophagy has important clinical benefits in patients affected by diverse cancer types. Currently, about 30 clinical trials are actively investigating the efficacy of autophagy modulators to enhance the efficacy of cytotoxic chemotherapy treatments. A deeper understanding of the molecular pathways regulating autophagy in the cancer context will provide new ways to target autophagy for improving the therapeutic benefits. Herein, we describe how autophagy participates during malignant transformation and cancer progression, and we report the ultimate efforts to translate this knowledge into specific therapeutic approaches to treat and cure human cancers.

Quantitative MRI phenotypes capture biological heterogeneity in multiple sclerosis patients

Magnetization transfer ratio (MTR) and brain volumetric imaging are (semi-)quantitative MRI markers capturing demyelination, axonal degeneration and/or inflammation. However, factors shaping variation in these traits are largely unknown. In this study, we collected a longitudinal cohort of 33 multiple sclerosis (MS) patients and extended it cross-sectionally to 213. We measured MTR in lesions, normal-appearing white matter (NAWM), normal-appearing grey matter (NAGM) and total brain, grey matter, white matter and lesion volume. We also calculated the polygenic MS risk score. Longitudinally, inter-patient differences at inclusion and intra-patient changes during follow-up together explained > 70% of variance in MRI, with inter-patient differences at inclusion being the predominant source of variance. Cross-sectionally, we observed a moderate correlation of MTR between NAGM and NAWM and, less pronounced, with lesions. Age and gender explained about 30% of variance in total brain and grey matter volume. However, they contributed less than 10% to variance in MTR measures. There were no significant associations between MRI traits and the genetic risk score. In conclusion, (semi-)quantitative MRI traits change with ongoing disease activity but this change is modest in comparison to pre-existing inter-patient differences. These traits reflect individual variation in biological processes, which appear different from those involved in genetic MS susceptibility.

An observation of primary production enhanced by coastal upwelling in the southwest East/Japan Sea

Abstract Coastal upwelling (CU) is an important process that causes changes in physical and chemical properties, resulting in variation of biological processes in a coastal area. In the southwestern part of the East/Japan Sea (SWES), CU has been alleged as one of the mechanisms responsible for higher net primary production (NPP) than the rest of the East/Japan Sea. We provide, for the first time, high spatial resolution underway observations of sea surface temperature, salinity, chlorophyll-a fluorescence and Δ(O2/Ar), revealing the physical and biological characteristics of the upwelled waters in the SWES. The cold, upwelled waters retained high fluorescence and Δ(O2/Ar), consistent with enhanced phytoplankton biomass and biological O2 production by CU. The net community production (NCP) in the ambient and upwelled waters were 33 ± 19 and 77 ± 41 mmol O2 m−2 d−1, respectively. The latter should be considered as a lower bound, containing a significant fraction of low O2 waters from subsurface. Satellite observation indicated that NPP in the upwelled waters were higher than the ambient waters by 51%. This implies that up to half of higher NPP in the SWES than the rest of the East/Japan Sea can be ascribed to CU events.

In vivo genome-wide binding interactions of mouse and human constitutive androstane receptors reveal novel gene targets.

The constitutive androstane receptor (CAR; NR1I3) is a nuclear receptor orchestrating complex roles in cell and systems biology. Species differences in CAR’s effector pathways remain poorly understood, including its role in regulating liver tumor promotion. We developed transgenic mouse models to assess genome-wide binding of mouse and human CAR, following receptor activation in liver with direct ligands and with phenobarbital, an indirect CAR activator. Genomic interaction profiles were integrated with transcriptional and biological pathway analyses. Newly identified CAR target genes included Gdf15 and Foxo3, important regulators of the carcinogenic process. Approximately 1000 genes exhibited differential binding interactions between mouse and human CAR, including the proto-oncogenes, Myc and Ikbke, which demonstrated preferential binding by mouse CAR as well as mouse CAR-selective transcriptional enhancement. The ChIP-exo analyses also identified distinct binding motifs for the respective mouse and human receptors. Together, the results provide new insights into the important roles that CAR contributes as a key modulator of numerous signaling pathways in mammalian organisms, presenting a genomic context that specifies species variation in biological processes under CAR’s control, including liver cell proliferation and tumor promotion.

Improving assessment of Pandalus stocks using a seasonal, size-structured assessment model with environmental variables. Part I: Model description and application

Pandalus species display the following features that make it difficult to apply traditional age-based stock assessment models: (i) difficulty of determining age in the absence of hard parts retained through the molt; (ii) sex change in which individuals mature first as males and then transform to females; and (iii) potentially strong influence of environmental conditions on recruitment population dynamics. In this context, we propose a seasonal, size-structured assessment model dedicated to stock assessment of hermaphroditic Pandalidae. The modeling framework incorporates a submodel for changes of length at sex transformation and functions to incorporate environmental effects on recruitment dynamics. The model can be directly fitted to length-structured data, overcoming the length to age conversion problem. The model has a seasonal time step that allows it to account for seasonal variations in biological processes and fishing patterns. The model provides stock assessment outputs, such as fishing mortality and stock biomass estimates, and sex-specific abundance-at-length. The model is applied to the exploited shrimp stock of Pandalus borealis in the Gulf of Maine as an example of its utility. The model proposed in this study is flexible and generic and can be applied to many other exploited stocks.

Epigenome overlap measure (EPOM) for comparing tissue/cell types based on chromatin states.

BackgroundThe dynamics of epigenomic marks in their relevant chromatin states regulate distinct gene expression patterns, biological functions and phenotypic variations in biological processes. The availability of high-throughput epigenomic data generated by next-generation sequencing technologies allows a data-driven approach to evaluate the similarities and differences of diverse tissue and cell types in terms of epigenomic features. While ChromImpute has allowed for the imputation of large-scale epigenomic information to yield more robust data to capture meaningful relationships between biological samples, widely used methods such as hierarchical clustering and correlation analysis cannot adequately utilize epigenomic data to accurately reveal the distinction and grouping of different tissue and cell types.MethodsWe utilize a three-step testing procedure–ANOVA, t test and overlap test to identify tissue/cell-type- associated enhancers and promoters and to calculate a newly defined Epigenomic Overlap Measure (EPOM). EPOM results in a clear correspondence map of biological samples from different tissue and cell types through comparison of epigenomic marks evaluated in their relevant chromatin states.ResultsCorrespondence maps by EPOM show strong capability in distinguishing and grouping different tissue and cell types and reveal biologically meaningful similarities between Heart and Muscle, Blood & T-cell and HSC & B-cell, Brain and Neurosphere, etc. The gene ontology enrichment analysis both supports and explains the discoveries made by EPOM and suggests that the associated enhancers and promoters demonstrate distinguishable functions across tissue and cell types. Moreover, the tissue/cell-type-associated enhancers and promoters show enrichment in the disease-related SNPs that are also associated with the corresponding tissue or cell types. This agreement suggests the potential of identifying causal genetic variants relevant to cell-type-specific diseases from our identified associated enhancers and promoters.ConclusionsThe proposed EPOM measure demonstrates superior capability in grouping and finding a clear correspondence map of biological samples from different tissue and cell types. The identified associated enhancers and promoters provide a comprehensive catalog to study distinct biological processes and disease variants in different tissue and cell types. Our results also find that the associated promoters exhibit more cell-type-specific functions than the associated enhancers do, suggesting that the non-associated promoters have more housekeeping functions than the non-associated enhancers.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2303-9) contains supplementary material, which is available to authorized users.

Survey of computational haplotype determination methods for single individual

Genome-wide association studies have expanded our understanding of the relationship between the human genome and disease. However, because of current technical limitations, it is still challenging to clearly resolve diploid sequences, that is, two copies for each chromosome. One copy of each chromosome is inherited from each parent and the genomic function is determined by the interplay between the alleles represented as genotypes in the diploid sequences. Thus, to understand the nature of genetic variation in biological processes, including disease, it is necessary to determine the complete genomic sequence of each haplotype. Although there are experimental approaches for haplotype sequencing that physically separate the chromosomes, these methods are expensive and laborious and require special equipment. Here, we review the computational approaches that can be used to determine the haplotype phase. Since 1990, many researchers have tried to reconstruct the haplotype phase using a variety of computational methods, and some researches have been successfully help to determine the haplotype phase. In this review, we investigate how the computational haplotype determination methods have been developed, and we present the remaining problems affecting the determination of the haplotype of single individual using next-generation sequencing methods.

A genetic strategy for probing the functional diversity of magnetosome formation.

Model genetic systems are invaluable, but limit us to understanding only a few organisms in detail, missing the variations in biological processes that are performed by related organisms. One such diverse process is the formation of magnetosome organelles by magnetotactic bacteria. Studies of model magnetotactic α-proteobacteria have demonstrated that magnetosomes are cubo-octahedral magnetite crystals that are synthesized within pre-existing membrane compartments derived from the inner membrane and orchestrated by a specific set of genes encoded within a genomic island. However, this model cannot explain all magnetosome formation, which is phenotypically and genetically diverse. For example, Desulfovibrio magneticus RS-1, a δ-proteobacterium for which we lack genetic tools, produces tooth-shaped magnetite crystals that may or may not be encased by a membrane with a magnetosome gene island that diverges significantly from those of the α-proteobacteria. To probe the functional diversity of magnetosome formation, we used modern sequencing technology to identify hits in RS-1 mutated with UV or chemical mutagens. We isolated and characterized mutant alleles of 10 magnetosome genes in RS-1, 7 of which are not found in the α-proteobacterial models. These findings have implications for our understanding of magnetosome formation in general and demonstrate the feasibility of applying a modern genetic approach to an organism for which classic genetic tools are not available.

The patterning of retinal horizontal cells: normalizing the regularity index enhances the detection of genomic linkage.

Retinal neurons are often arranged as non-random distributions called “mosaics,” as their somata minimize proximity to neighboring cells of the same type. The horizontal cells serve as an example of such a mosaic, but little is known about the developmental mechanisms that underlie their patterning. To identify genes involved in this process, we have used three different spatial statistics to assess the patterning of the horizontal cell mosaic across a panel of genetically distinct recombinant inbred strains. To avoid the confounding effect of cell density, which varies twofold across these different strains, we computed the “real/random regularity ratio,” expressing the regularity of a mosaic relative to a randomly distributed simulation of similarly sized cells. To test whether this latter statistic better reflects the variation in biological processes that contribute to horizontal cell spacing, we subsequently compared the genomic linkage for each of these two traits, the regularity index, and the real/random regularity ratio, each computed from the distribution of nearest neighbor (NN) distances and from the Voronoi domain (VD) areas. Finally, we compared each of these analyses with another index of patterning, the packing factor. Variation in the regularity indexes, as well as their real/random regularity ratios, and the packing factor, mapped quantitative trait loci to the distal ends of Chromosomes 1 and 14. For the NN and VD analyses, we found that the degree of linkage was greater when using the real/random regularity ratio rather than the respective regularity index. Using informatic resources, we narrowed the list of prospective genes positioned at these two intervals to a small collection of six genes that warrant further investigation to determine their potential role in shaping the patterning of the horizontal cell mosaic.

Seasonal Variation and Trends in Stroke Hospitalizations and Mortality in a South American Community Hospital

Numerous studies have reported the presence of temporal variations in biological processes. Seasonal variation (SV) in stroke has been widely studied, but little data have been published on this phenomenon in the Southern Hemisphere, and there have been no studies reported from Argentina. The goals of the present study were to describe the SV of admissions and deaths for stroke and examine trends in stroke morbidity and mortality over a 3-year period in a community hospital in Argentina. Hospital discharge reports from the electronic database of vital statistics between 1999 and 2001 were examined retrospectively. Patients who had a main discharge diagnosis of stroke (ischemic or hemorrhagic) or cerebrovascular accident (International Classification of Diseases, Ninth Revision codes 431, 432, 434, and 436) were selected. The study sample included 1382 hospitalizations by stroke (3.5% of all admissions). In-hospital mortality demonstrated a winter peak (25.5% vs 17% in summer; P = .001). The crude seasonal stroke attack rate (ischemic and hemorrhagic) was highest in winter (164 per 100,000 population; 95% CI, 159-169 per 100,000) and lowest in summer (124 per 100,000; 95% CI, 120-127 per 100,000; P = .008). Stroke admissions followed a seasonal pattern, with a winter-spring predominance (P = .008). Our data indicate a clear SV in stroke deaths and admissions in this region of Argentina. The existence of SV in stroke raises a different hypothesis about the rationale of HF admissions and provides information for the organization of care and resource allocation.

RNAi pathway integration in Caenorhabditis elegans development

In this review, the pathways involving small RNAs are provided followed by a new and updated network that illustrates their interplay with diverse cellular mechanisms in Caenorhabditis elegans. The RNA silencing pathways are now recognized as key factors that connect together the many variations in biological processes, including transcriptional gene regulation, post-transcriptional gene silencing, translational gene silencing, apoptosis, meiosis, and antiviral defense. The utilization of small RNAs represents a specific, energy conserving, and fast mechanism of gene regulation via a core system known as RNA interference.

Light-dark oscillations in the lung transcriptome: implications for lung homeostasis, repair, metabolism, disease, and drug action

Diurnal-nocturnal, or circadian-like, rhythms are 24-h variations in biological processes, evolved for the efficient functioning of living organisms. Such oscillations and their regulation in many peripheral tissues are still unclear. In this study, we used Affymetrix gene chips in a rich time-series experiment involving 54 animals killed at 18 time points within the 24-h cycle to examine light-dark cycle patterns of gene expression in rat lungs. Data mining identified 646 genes (represented by 1,006 probe sets) showing robust oscillations in expression in lung that were parsed into 8 distinct temporal clusters. Surprisingly, more than two-thirds of the probe sets showing cyclic expression peaked during the animal's light/inactive period. Six core clock genes and nine clock-related genes showed rhythmic oscillations in their expression in lung. Many of the genes that peaked during the inactive period included genes related to extracellular matrix, cytoskeleton, and protein processing and trafficking, which appear to be mainly involved in the repair and remodeling of the organ. Genes coding for growth factor ligands and their receptors, which play important roles in maintaining normal lung function, also showed rhythmic expression. In addition, genes involved in the metabolism and transport of endogenous compounds, xenobiotics, and therapeutic drugs, along with genes that are biomarkers or potential therapeutic targets for many lung diseases, also exhibited 24-h cyclic oscillations, suggesting an important role for such rhythms in regulating various aspects of the physiology and pathophysiology of lung.

Circadian Variations in Rat Liver Gene Expression: Relationships to Drug Actions

Chronopharmacology is an important but under-explored aspect of therapeutics. Rhythmic variations in biological processes can influence drug action, including pharmacodynamic responses, due to circadian variations in the availability or functioning of drug targets. We hypothesized that global gene expression analysis can be useful in the identification of circadian-regulated genes involved in drug action. Circadian variations in gene expression in rat liver were explored using Affymetrix gene arrays. A rich time series involving animals analyzed at 18 time points within the 24-h cycle was generated. Of the more than 15,000 probe sets on these arrays, 265 exhibited oscillations with a 24-h frequency. Cluster analysis yielded five distinct circadian clusters, with approximately two thirds of the transcripts reaching maximal expression during the dark/active period of the animal. Of the 265 probe sets, 107 were identified as having potential therapeutic importance. The expression levels of clock genes were also investigated in this study. Five clock genes exhibited circadian variation in the liver, and data suggest that these genes may also be regulated by corticosteroids.

Modeling analysis of the effect of iron enrichment on dimethyl sulfide dynamics in the NE Pacific (SERIES experiment)

The large‐scale iron enrichment conducted in the NE Pacific during the Subarctic Ecosystem Response to Iron Enrichment Study (SERIES) triggered a phytoplankton bloom dominated successively by nanophytoplankton and large diatoms. During the first 14 days, surface dimethyl sulfide (DMS) levels increased both inside (up to 22 nmol L−1) and outside (up to 19 nmol L−1) the patch, with no consistent Fe effect. Later, DMS concentrations became sixfold lower inside the patch than outside. In this study, we used a DMS budget module embedded in a one‐dimensional ocean turbulence model to investigate the contribution of the interacting physical, photochemical, and biological processes to this particular DMS response. Temporal variations in biological net DMS production were reconstructed using an inverse modeling approach. Our results show that short‐term (days) variations in both the physical processes (i.e., turbulent mixing and ventilation) and the biological cycling of DMS are needed to explain the time evolution of DMS concentrations both outside and inside the Fe‐enriched patch. The biological net DMS production was generally high (up to 0.35 nmol L−1 h−1) and comparable outside and inside the patch during the first 10 days, corresponding to the observed accumulation of DMS inside and outside the patch. Later, it became negative (net DMS biological consumption) inside the patch, suggesting a change in dimethylsulfoniopropionate bacterial metabolism. This study stresses the importance of short‐term variations in biological processes and their sensitivity to the physical environment in shaping the DMS response to iron enrichment.