A varying-coefficient model for the analysis of methylation sequencing data.

DNA methylation is an important epigenetic modification involved in gene regulation. Advances in the next generation sequencing technology have enabled the retrieval of DNA methylation information at single-base-resolution. However, due to the sequencing process and the limited amount of isolated DNA, DNA-methylation-data are often noisy and sparse, which complicates the identification of differentially methylated regions (DMRs), especially when few replicates are available. We present a varying-coefficient model for detecting DMRs by using single-base-resolved methylation information. The model simultaneously smooths the methylation profiles and allows detection of DMRs, while accounting for additional covariates. The proposed model takes into account possible overdispersion by using a beta-binomial distribution. The overdispersion itself can be modeled as a function of the genomic region and explanatory variables. We illustrate the properties of the proposed model by applying it to two real-life case studies.

Facilitating clinical use of the Amsterdam Instrumental Activities of Daily Living Questionnaire: Normative data and a diagnostic cutoff value.

OBJECTIVE: The Amsterdam Instrumental Activities of Daily Living Questionnaire (A-IADL-Q) is well validated and commonly used to assess difficulties in everyday functioning regarding dementia. To facilitate interpretation and clinical implementation across different European countries, we aim to provide normative data and a diagnostic cutoff for dementia. METHODS: Cross-sectional data from Dutch Brain Research Registry (N = 1,064; mean (M) age = 62 ± 11 year; 69.5% female), European Medial Information Framework-Alzheimer's Disease 90 + (N = 63; Mage = 92 ± 2 year; 52.4% female), and European Prevention of Alzheimer's Dementia Longitudinal Cohort Study (N = 247; Mage = 63 ± 7 year; 72.1% female) were used. The generalized additive models for location, scale, and shape framework were used to obtain normative values (Z-scores). The beta distribution was applied, and combinations of age, sex, and educational attainment were modeled. The optimal cutoff for dementia was calculated using area under receiver operating curves (AUC-ROC) and Youden Index, using data from Amsterdam Dementia Cohort (N = 2,511, Mage = 64 ± 8 year, 44.4% female). RESULTS: The best normative model accounted for a cubic-like decrease of IADL performance with age that was more pronounced in low compared to medium/high educational attainment. The cutoff for dementia was 1.85 standard deviation below the population mean (AUC = 0.97; 95% CI [0.97-0.98]). CONCLUSION: We provide regression-based norms for A-IADL-Q and a diagnostic cutoff for dementia, which help improve clinical assessment of IADL performance across European countries.

Unveiling the Molecular Mechanism of Trastuzumab Resistance in SKBR3 and BT474 Cell Lines for HER2 Positive Breast Cancer.

HER2-positive breast cancer is one of the most prevalent forms of cancer among women worldwide. Generally, the molecular characteristics of this breast cancer include activation of human epidermal growth factor receptor-2 (HER2) and hormone receptor activation. HER2-positive is associated with a higher death rate, which led to the development of a monoclonal antibody called trastuzumab, specifically targeting HER2. The success rate of HER2-positive breast cancer treatment has been increased; however, drug resistance remains a challenge. This fact motivated us to explore the underlying molecular mechanisms of trastuzumab resistance. For this purpose, a two-fold approach was taken by considering well-known breast cancer cell lines SKBR3 and BT474. In the first fold, trastuzumab treatment doses were optimized separately for both cell lines. This was done based on the proliferation rate of cells in response to a wide variety of medication dosages. Thereafter, each cell line was cultivated with a steady dosage of herceptin for several months. During this period, six time points were selected for further in vitro analysis, ranging from the untreated cell line at the beginning to a fully resistant cell line at the end of the experiment. In the second fold, nucleic acids were extracted for further high throughput-based microarray experiments of gene and microRNA expression. Such expression data were further analyzed in order to infer the molecular mechanisms involved in the underlying development of trastuzumab resistance. In the list of differentially expressed genes and miRNAs, multiple genes (e.g., BIRC5, E2F1, TFRC, and USP1) and miRNAs (e.g., hsa miR 574 3p, hsa miR 4530, and hsa miR 197 3p) responsible for trastuzumab resistance were found. Downstream analysis showed that TFRC, E2F1, and USP1 were also targeted by hsa-miR-8485. Moreover, it indicated that miR-4701-5p was highly expressed as compared to TFRC in the SKBR3 cell line. These results unveil key genes and miRNAs as molecular regulators for trastuzumab resistance.

Differentiation between chemo- and radiotoxicity of 137Cs and 60Co on Lemna minor.

The uptake and effects of stable Cs and Co on L.minor were extensively studied, together with the effects of gamma radiation using a 137Cs or 60Co source. Innovative is that we combined external irradiation (from 137Cs or 60Co sources) with the direct uptake of certain amounts of stable Cs or Co to simulate the impact of the same mass of a radioisotope compared with that of the stable element. Such approach allows to differentiate between chemo- and radiotoxicity of 137Cs or 60Co, permitting to study the 137Cs and 60Co uptake by L. minor without using high concentrations of these elements in solution. Our results indicate that radiotoxicity of both 137Cs and 60Co has a greater importance compared to their chemotoxicity. This was also supported by the independent action and concentration addition concepts. Both concepts resulted in a good prediction of the dose-response curve of the combination exposure. The maximal removal of 137Cs or 60Co per gram dry matter of L. minor was lower compared with the removal of the corresponding stable isotope. The toxicity of 60Co was higher compared to 137Cs based on EC50 values and uptake data. With respect to the effects on photosynthetic pigments, starch and soluble sugars contents, only starch increased in a concentration- and dose-dependent manner.

Safety of Accelerated Infliximab Infusions in Children With Inflammatory Bowel Disease: A Retrospective Cohort Study.

OBJECTIVES: Accelerated infliximab (IFX) infusions have shown to be safe in adults with inflammatory bowel disease (IBD), but data on its safety in pediatric IBD is limited. This study aimed to assess the incidence and timing of infusion reactions (IR) in children with IBD who received accelerated (1-h) versus standard (2-h) IFX infusions. METHODS: This retrospective cohort study included IBD patients 4-18 years of age and initiated IFX between January 2006 and November 2021 at Amsterdam University Medical Centre, location Academic Medical Centre (AMC) and VU Medical Centre (VUmc). The AMC protocol was adjusted in July 2019 from standard to accelerated infusions with 1-h intrahospital post-infusion observation period, whereas in VUmc only standard infusions were administered without an observation period. After merging the departments in 2022, all VUmc patients were allocated to the accelerated infusions (AMC) protocol. Primary outcome was the incidence of acute IR among maintenance accelerated versus standard infusions. RESULTS: Totally, 297 (150 VUmc, 147 AMC) patients (221 Crohn disease; 65 ulcerative colitis; 11 IBD-unclassified) with cumulative n = 8381 IFX infusions were included. No statistically significant difference in the per-infusion incidence of IR was observed between maintenance standard infusions (26/4383, 0.6% of infusions) and accelerated infusions (9/3117, 0.3%) ( P = 0.33). Twenty-six of 35 IR (74%) occurred during the infusion, while 9 occurred post-infusion (26%). Only 3 of 9 IR developed in the intrahospital observation period following the switch to accelerated infusions. All post-infusion IR were mild, requiring no intervention or only oral medication. CONCLUSIONS: Accelerated IFX infusion without a post-infusion observation period for children with IBD seems a safe approach.

The isotope distribution: A rose with thorns.

The isotope distribution, which reflects the number and probabilities of occurrence of different isotopologues of a molecule, can be theoretically calculated. With the current generation of (ultra)-high-resolution mass spectrometers, the isotope distribution of molecules can be measured with high sensitivity, resolution, and mass accuracy. However, the observed isotope distribution can differ substantially from the expected isotope distribution. Although differences between the observed and expected isotope distribution can complicate the analysis and interpretation of mass spectral data, they can be helpful in a number of specific applications. These applications include, yet are not limited to, the identification of peptides in proteomics, elucidation of the elemental composition of small organic molecules and metabolites, as well as wading through peaks in mass spectra of complex bioorganic mixtures such as petroleum and humus. In this review, we give a nonexhaustive overview of factors that have an impact on the observed isotope distribution, such as elemental isotope deviations, ion sampling, ion interactions, electronic noise and dephasing, centroiding, and apodization. These factors occur at different stages of obtaining the isotope distribution: during the collection of the sample, during the ionization and intake of a molecule in a mass spectrometer, during the mass separation and detection of ionized molecules, and during signal processing.

Machine learning approach for the prediction of the number of sulphur atoms in peptides using the theoretical aggregated isotope distribution.

RATIONALE: The observed isotope distribution is an important attribute for the identification of peptides and proteins in mass spectrometry-based proteomics. Sulphur atoms have a very distinctive elemental isotope definition, and therefore, the presence of sulphur atoms has a substantial effect on the isotope distribution of biomolecules. Hence, knowledge of the number of sulphur atoms can improve the identification of peptides and proteins. METHODS: In this paper, we conducted a theoretical investigation on the isotope properties of sulphur-containing peptides. We proposed a gradient boosting approach to predict the number of sulphur atoms based on the aggregated isotope distribution. We compared prediction accuracy and assessed the predictive power of the features using the mass and isotope abundance information from the first three, five and eight aggregated isotope peaks. RESULTS: Mass features alone are not sufficient to accurately predict the number of sulphur atoms. However, we reach near-perfect prediction when we include isotope abundance features. The abundance ratios of the eighth and the seventh, the fifth and the fourth, and the third and the second aggregated isotope peaks are the most important abundance features. The mass difference between the eighth, the fifth or the third aggregated isotope peaks and the monoisotopic peak are the most predictive mass features. CONCLUSIONS: Based on the validation analysis it can be concluded that the prediction of the number of sulphur atoms based on the isotope profile fails, because the isotope ratios are not measured accurately. These results indicate that it is valuable for future instrument developments to focus more on improving spectral accuracy to measure peak intensities of higher-order isotope peaks more accurately.

The Effects of Combined Exposure to Simulated Microgravity, Ionizing Radiation, and Cortisol on the In Vitro Wound Healing Process.

Human spaceflight is associated with several health-related issues as a result of long-term exposure to microgravity, ionizing radiation, and higher levels of psychological stress. Frequent reported skin problems in space include rashes, itches, and a delayed wound healing. Access to space is restricted by financial and logistical issues; as a consequence, experimental sample sizes are often small, which limits the generalization of the results. Earth-based simulation models can be used to investigate cellular responses as a result of exposure to certain spaceflight stressors. Here, we describe the development of an in vitro model of the simulated spaceflight environment, which we used to investigate the combined effect of simulated microgravity using the random positioning machine (RPM), ionizing radiation, and stress hormones on the wound-healing capacity of human dermal fibroblasts. Fibroblasts were exposed to cortisol, after which they were irradiated with different radiation qualities (including X-rays, protons, carbon ions, and iron ions) followed by exposure to simulated microgravity using a random positioning machine (RPM). Data related to the inflammatory, proliferation, and remodeling phase of wound healing has been collected. Results show that spaceflight stressors can interfere with the wound healing process at any phase. Moreover, several interactions between the different spaceflight stressors were found. This highlights the complexity that needs to be taken into account when studying the effect of spaceflight stressors on certain biological processes and for the aim of countermeasures development.

Fractionated irradiation of MCF7 breast cancer cells rewires a gene regulatory circuit towards a treatment-resistant stemness phenotype.

Radiotherapy is the standard of care for breast cancer. However, surviving radioresistant cells can repopulate following treatment and provoke relapse. Better understanding of the molecular mechanisms of radiation resistance may help to improve treatment of radioresistant tumours. To emulate radiation therapy at the cellular level, we exposed MCF7 breast cancer cells to daily radiation doses of 2 Gy up to an accumulated dose of 20 Gy. Fractionally irradiated cells (FIR20) displayed increased clonogenic survival and population doubling time as compared with age-matched sham-irradiated cells and untreated parental MCF7 cells. RNA-sequencing revealed a core signature of 229 mRNAs and 7 circular RNAs of which the expression was significantly altered in FIR20 cells. Dysregulation of several top genes was mirrored at the protein level. The FIR20 cell transcriptome overlapped significantly with canonical radiation response signatures and demonstrated a remarkable commonality with radiation and endocrine therapy resistance expression profiles, suggesting crosstalk between both acquired resistance pathways, as indicated by reduced sensitivity to tamoxifen cytotoxicity of FIR20 cells. Using predictive analyses and functional enrichment, we identified a gene-regulatory network that promotes stemness and inflammatory signalling in FIR20 cells. We propose that these phenotypic traits render breast cancer cells more radioresistant but may at the same time serve as potential targets for combination therapies.

Accurate prediction of metagenome-assembled genome completeness by MAGISTA, a random forest model built on alignment-free intra-bin statistics.

BACKGROUND: Although the total number of microbial taxa on Earth is under debate, it is clear that only a small fraction of these has been cultivated and validly named. Evidently, the inability to culture most bacteria outside of very specific conditions severely limits their characterization and further studies. In the last decade, a major part of the solution to this problem has been the use of metagenome sequencing, whereby the DNA of an entire microbial community is sequenced, followed by the in silico reconstruction of genomes of its novel component species. The large discrepancy between the number of sequenced type strain genomes (around 12,000) and total microbial diversity (106-1012 species) directs these efforts to de novo assembly and binning. Unfortunately, these steps are error-prone and as such, the results have to be intensely scrutinized to avoid publishing incomplete and low-quality genomes. RESULTS: We developed MAGISTA (metagenome-assembled genome intra-bin statistics assessment), a novel approach to assess metagenome-assembled genome quality that tackles some of the often-neglected drawbacks of current reference gene-based methods. MAGISTA is based on alignment-free distance distributions between contig fragments within metagenomic bins, rather than a set of reference genes. For proper training, a highly complex genomic DNA mock community was needed and constructed by pooling genomic DNA of 227 bacterial strains, specifically selected to obtain a wide variety representing the major phylogenetic lineages of cultivable bacteria. CONCLUSIONS: MAGISTA achieved a 20% reduction in root-mean-square error in comparison to the marker gene approach when tested on publicly available mock metagenomes. Furthermore, our highly complex genomic DNA mock community is a very valuable tool for benchmarking (new) metagenome analysis methods.

Fecal Amino Acid Analysis in Newly Diagnosed Pediatric Inflammatory Bowel Disease: A Multicenter Case-Control Study.

BACKGROUND: Fecal metabolomic profiles differ between pediatric inflammatory bowel disease (IBD) patients and controls and may provide new insights in the pathophysiology of IBD. The role of amino acids, however, is not fully elucidated. We aimed to assess fecal amino acid profiles in pediatric IBD. METHODS: In this case-control study, treatment-naïve, newly diagnosed pediatric IBD patients and a non-IBD control group, matched based on sex and age, were included in 2 tertiary centres. Fecal amino acid profiles were assessed using a targeted high-performance liquid chromatography technique. A random forest classifier method was used to develop a prediction model differentiating IBD from controls and predicting IBD phenotype. The association between IBD localization and amino acid concentrations was tested with ordinal regression models. RESULTS: We included 78 newly diagnosed IBD patients (40 Crohn's disease [CD], 38 ulcerative colitis [UC]) and 105 controls. Patients with IBD could be differentiated from controls with an accuracy of 82% (sensitivity 63%, specificity 97%). Twenty-nine out of the 42 measured unique amino acids were included in the prediction model. Increased levels of tryptophan, taurine, alanine, ornithine, valine, histidine, and leucine were the most differentiating features. Children with CD and UC could be differentiated from the controls with an accuracy of 80% and 90%, respectively. Inflammatory bowel disease phenotype could not be predicted. Tryptophan, valine, and histidine levels were positively associated with more extended disease in UC patients (P < .05). CONCLUSIONS: Fecal amino acids may enhance understanding of the role of host-microbial interactions in the pathophysiology of IBD and may evolve into biomarkers for pediatric IBD diagnostic and personalized medicine.

Fecal amino acid analysis could differentiate newly diagnosed children with IBD from a non-IBD control group with an accuracy of 82%. Increased levels of tryptophan, taurine, alanine, ornithine, and valine were the most differentiating features. This may enhance understanding of IBD pathophysiology.

Moderated Test Statistics to Detect Differential Deuteration in Hydrogen/Deuterium Exchange Mass Spectrometry Experiments.

With differential hydrogen/deuterium exchange, differences in the structure and dynamics of protein states can be studied. Detecting statistically significant differentially deuterated peptides is crucial to draw meaningful conclusions about the distinct conformations and dynamics of the protein under study. Here, we introduced a linear model in combination with an empirical Bayes approach to detect differentially deuterated peptides. Using a linear model allows one to test for differences in deuteration between two (two-sample t-test) or more groups (F-statistic), while potentially controlling for the effects of other variables that are not of interest. The empirical Bayes approach improves the estimation of deuteration-level variances, especially in experiments with a low number of replicates. As a consequence, the two sample t-tests and the F-statistic become moderated, resulting in a lower number of false positive and false negative findings. Furthermore, we introduce a thresholded-moderated t-statistic to test if the observed deuteration differences are larger than a specified, biologically relevant difference. Finally, we underline the importance of having a sufficient number of replicates, and the effect of the number of replicates on the power of the statistical significance tests. The R-code for the proposed moderated test statistics is available upon request.

Effects of environmental parameters on Lemna minor growth: An integrated experimental and modelling approach.

Pollution of surface waters is a worldwide problem for people and wildlife. Remediation and phytoremediation approaches can offer a solution to deal with specific scenarios. Lemna minor, commonly known as duckweed, can absorb and accumulate pollutants in its biomass. To evaluate if L. minor could be applied for phytoremediation purposes, it is necessary to further investigate its remediation capability and to identify which parameters affect the remediation process. Such a model must include both plant growth and pollutant exchange. A remediation model based on a robust experimental study can help to evaluate L. minor as a proper remediation strategy and to predict the outcome of a L. minor based remediation system. To set up this model, this paper focusses on a detailed experimental study and a comprehensive mathematical modelling approach to represent L. minor growth as a function of biomass, temperature, light irradiation and variable nutrient concentrations. The influence of environmental conditions on L. minor growth was studied, by composing 7 days growth curves. Plants were grown under predefined environmental conditions (25°C, 14h photoperiod, 220 µmol m-2 s-1 light intensity and a modified Hoagland solution with 23.94 mg N L-1 and 3.10 mg P L-1 (N:P ratio of 7.73)) as standard for all experiments. The influence of different temperatures (6, 10, 15, 20, 25, 30 and 35°C), light intensities (63, 118, 170, 220 and 262 µmol m-2 s-1), photoperiods (12h and 14h) and N:P ratios (1.18, 3.36, 7.73 and 29.57) were tested in the model. As a result, a growth model was optimised using separate datasets for temperature, light intensity, photoperiod and nutrients and validated by further integrated testing. The growth model is a stable platform for application in phytoremediation of radionuclides in contaminated water, to be extended in future studies with information of pollutant uptake, pollutant-nutrient interactions and transfer to the biomass.

Predicting the number of sulfur atoms in peptides and small proteins based on the observed aggregated isotope distribution.

RATIONALE: Identification of peptides and proteins is a challenging task in mass spectrometry-based proteomics. Knowledge of the number of sulfur atoms can improve the identification of peptides and proteins. METHODS: In this article, we propose a method for the prediction of S-atoms based on the aggregated isotope distribution. The Mahalanobis distance is used as dissimilarity measure to compare mass- and intensity-based features from the observed and theoretical isotope distributions. RESULTS: The relative abundance of the second and the third aggregated isotopic variants (as compared to the monoisotopic one) and the mass difference between the second and third aggregated isotopic variants are the most important features to predict the number of S-atoms. CONCLUSIONS: The mass and intensity accuracies of the observed aggregated isotopic variants are insufficient to accurately predict the number of atoms. However, using a limited set of predictions for a peptide, rather than predicting a single number of S-atoms, has a reasonably high prediction accuracy.

Soil microbial community structure and functionality changes in response to long-term metal and radionuclide pollution.

Microbial communities are essential for a healthy soil ecosystem. Metals and radionuclides can exert a persistent pressure on the soil microbial community. However, little is known on the effect of long-term co-contamination of metals and radionuclides on the microbial community structure and functionality. We investigated the impact of historical discharges of the phosphate and nuclear industry on the microbial community in the Grote Nete river basin in Belgium. Eight locations were sampled along a transect to the river edge and one location further in the field. Chemical analysis demonstrated a metal and radionuclide contamination gradient and revealed a distinct clustering of the locations based on all metadata. Moreover, a relation between the chemical parameters and the bacterial community structure was demonstrated. Although no difference in biomass was observed between locations, cultivation-dependent experiments showed that communities from contaminated locations survived better on singular metals than communities from control locations. Furthermore, nitrification, a key soil ecosystem process seemed affected in contaminated locations when combining metadata with microbial profiling. These results indicate that long-term metal and radionuclide pollution impacts the microbial community structure and functionality and provides important fundamental insights into microbial community dynamics in co-metal-radionuclide contaminated sites.

Deuteros 2.0: peptide-level significance testing of data from hydrogen deuterium exchange mass spectrometry.

SUMMARY: Hydrogen deuterium exchange mass spectrometry (HDX-MS) is becoming increasing routine for monitoring changes in the structural dynamics of proteins. Differential HDX-MS allows comparison of protein states, such as in the absence or presence of a ligand. This can be used to attribute changes in conformation to binding events, allowing the mapping of entire conformational networks. As such, the number of necessary cross-state comparisons quickly increases as additional states are introduced to the system of study. There are currently very few software packages available that offer quick and informative comparison of HDX-MS datasets and even fewer which offer statistical analysis and advanced visualization. Following the feedback from our original software Deuteros, we present Deuteros 2.0 which has been redesigned from the ground up to fulfill a greater role in the HDX-MS analysis pipeline. Deuteros 2.0 features a repertoire of facilities for back exchange correction, data summarization, peptide-level statistical analysis and advanced data plotting features. AVAILABILITY AND IMPLEMENTATION: Deuteros 2.0 can be downloaded for both Windows and MacOS from https://github.com/andymlau/Deuteros_2.0 under the Apache 2.0 license.

Intestinal mucositis precedes dysbiosis in a mouse model for pelvic irradiation.

Pelvic radiotherapy is known to evoke intestinal mucositis and dysbiosis. Currently, there are no effective therapies available to mitigate these injuries, which is partly due to a lack of insight into the events causing mucositis and dysbiosis. Here, the complex interplay between the murine host and its microbiome following pelvic irradiation was mapped by characterizing intestinal mucositis along with extensive 16S microbial profiling. We demonstrated important morphological and inflammatory implications within one day after exposure, thereby impairing intestinal functionality and inducing translocation of intraluminal bacteria into mesenteric lymph nodes as innovatively quantified by flow cytometry. Concurrent 16S microbial profiling revealed a delayed impact of pelvic irradiation on beta diversity. Analysis of composition of microbiomes identified biomarkers for pelvic irradiation. Among them, members of the families Ruminococcaceae, Lachnospiraceae and Porphyromonadaceae were differentially affected. Altogether, our unprecedented findings showed how pelvic irradiation evoked structural and functional changes in the intestine, which secondarily resulted in a microbiome shift. Therefore, the presented in vivo irradiation-gut-microbiome platform allows further research into the pathobiology of pelvic irradiation-induced intestinal mucositis and resultant dysbiosis, as well as the exploration of mitigating treatments including drugs and food supplements.

A "Refined Hydrogen Rule" and a "Refined Hydrogen and Halogen Rule" for Organic Molecules.

Deriving chemical formulas of organic molecules, based on spectral information, with heuristic rules is a commonly recurring task. The computational effort and the potentially extensive list of candidate formulas put a strain on the downstream analysis. In this paper, we introduce a set of redefined heuristics based on the hydrogen and halogen rules that reduce the computational burden and the number of candidate formulas for organic molecules, such as peptides and lipids.

Copper Resistance Mediates Long-Term Survival of Cupriavidus metallidurans in Wet Contact With Metallic Copper.

Metallic copper to combat bacterial proliferation in drinking water systems is being investigated as an attractive alternative to existing strategies. A potential obstacle to this approach is the induction of metal resistance mechanisms in contaminating bacteria, that could severely impact inactivation efficacy. Thus far, the role of these resistance mechanisms has not been studied in conditions relevant to drinking water systems. Therefore, we evaluated the inactivation kinetics of Cupriavidus metallidurans CH34 in contact with metallic copper in drinking water. Viability and membrane permeability were examined for 9 days through viable counts and flow cytometry. After an initial drop in viable count, a significant recovery was observed starting after 48 h. This behavior could be explained by either a recovery from an injured/viable-but-non-culturable state or regrowth of surviving cells metabolizing lysed cells. Either hypothesis would necessitate an induction of copper resistance mechanisms, since no recovery was seen in a CH34 mutant strain lacking metal resistance mechanisms, while being more pronounced when copper resistance mechanisms were pre-induced. Interestingly, no biofilms were formed on the copper surface, while extensive biofilm formation was observed on the stainless steel control plates. When CH34 cells in water were supplied with CuSO4, a similar initial decrease in viable counts was observed, but cells recovered fully after 7 days. In conclusion, we have shown that long-term bacterial survival in the presence of a copper surface is possible upon the induction of metal resistance mechanisms. This observation may have important consequences in the context of the increasing use of copper as an antimicrobial surface, especially in light of potential co-selection for metal and antimicrobial resistance.

A Conceptual Framework for Abundance Estimation of Genomic Targets in the Presence of Ambiguous Short Sequencing Reads.

RNA sequencing (RNA-seq) is widely used to study gene-, transcript-, or exon expression. To quantify the expression level, millions of short sequenced reads need to be mapped back to a reference genome or transcriptome. Read mapping makes it possible to find a location to which a read is identical or similar. Based upon this alignment, expression summaries, that is, read counts are generated. However, reads may be matched to multiple locations. Such ambiguously mapped reads are often ignored in the analysis, which is a potential loss of information and may cause bias in expression estimation. We present the general principles underlying multiread allocation and unbiased estimation of the expression level of genes, exons, or transcripts in the presence of multiple mapped reads. The underlying principles are derived from a theoretical concept that identifies important sources of information such as the number of uniquely mapped reads, the total target length, and the length of the shared target regions. We show with simulation studies that methods incorporating some or all of the aforementioned sources of information estimate the expression levels of genes, exons, and/or transcripts with a higher precision and accuracy than methods that do not use this information. We identify important sources of information that should be taken into account by methods that estimate the abundance of genes, exons, and/or transcripts to achieve good precision and accuracy.