BactImAS: a platform for processing and analysis of bacterial time-lapse microscopy movies

Background

The software available to date for analyzing image sequences from time-lapse microscopy works only for certain bacteria and under limited conditions. These programs, mostly MATLAB-based, fail for microbes with irregular shape, indistinct cell division sites, or that grow in closely packed microcolonies. Unfortunately, many organisms of interest have these characteristics, and analyzing their image sequences has been limited to time consuming manual processing.

Results

Here we describe BactImAS – a modular, multi-platform, open-source, Java-based software delivered both as a standalone program and as a plugin for Icy. The software is designed for extracting and visualizing quantitative data from bacterial time-lapse movies. BactImAS uses a semi-automated approach where the user defines initial cells, identifies cell division events, and, if necessary, manually corrects cell segmentation with the help of user-friendly GUI and incorporated ImageJ application. The program segments and tracks cells using a newly-developed algorithm designed for movies with difficult-to-segment cells that exhibit small frame-to-frame differences. Measurements are extracted from images in a configurable, automated fashion and an SQLite database is used to store, retrieve, and exchange all acquired data. Finally, the BactImAS can generate configurable lineage tree visualizations and export data as CSV files. We tested BactImAS on time-lapse movies of Mycobacterium smegmatis and achieved at least 10-fold reduction of processing time compared to manual analysis. We illustrate the power of the visualization tool by showing heterogeneity of both icl expression and cell growth atop of a lineage tree.

Conclusions

The presented software simplifies quantitative analysis of time-lapse movies overall and is currently the only available software for the analysis of mycobacteria-like cells. It will be of interest to the community of both end-users and developers of time-lapse microscopy software.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-251) contains supplementary material, which is available to authorized users.     

Scalable transcriptome preparation for massive parallel sequencing

Background

The tremendous output of massive parallel sequencing technologies requires automated robust and scalable sample preparation methods to fully exploit the new sequence capacity.

Methodology

In this study, a method for automated library preparation of RNA prior to massively parallel sequencing is presented. The automated protocol uses precipitation onto carboxylic acid paramagnetic beads for purification and size selection of both RNA and DNA. The automated sample preparation was compared to the standard manual sample preparation.

Conclusion/Significance

The automated procedure was used to generate libraries for gene expression profiling on the Illumina HiSeq 2000 platform with the capacity of 12 samples per preparation with a significantly improved throughput compared to the standard manual preparation. The data analysis shows consistent gene expression profiles in terms of sensitivity and quantification of gene expression between the two library preparation methods.     

A Multi-Atlas Based Method for Automated Anatomical Rat Brain MRI Segmentation and Extraction of PET Activity

Introduction

Preclinical in vivo imaging requires precise and reproducible delineation of brain structures. Manual segmentation is time consuming and operator dependent. Automated segmentation as usually performed via single atlas registration fails to account for anatomo-physiological variability. We present, evaluate, and make available a multi-atlas approach for automatically segmenting rat brain MRI and extracting PET activies.

Methods

High-resolution 7T 2DT2 MR images of 12 Sprague-Dawley rat brains were manually segmented into 27-VOI label volumes using detailed protocols. Automated methods were developed with 7/12 atlas datasets, i.e. the MRIs and their associated label volumes. MRIs were registered to a common space, where an MRI template and a maximum probability atlas were created. Three automated methods were tested: 1/registering individual MRIs to the template, and using a single atlas (SA), 2/using the maximum probability atlas (MP), and 3/registering the MRIs from the multi-atlas dataset to an individual MRI, propagating the label volumes and fusing them in individual MRI space (propagation & fusion, PF). Evaluation was performed on the five remaining rats which additionally underwent [¹⁸F]FDG PET. Automated and manual segmentations were compared for morphometric performance (assessed by comparing volume bias and Dice overlap index) and functional performance (evaluated by comparing extracted PET measures).

Results

Only the SA method showed volume bias. Dice indices were significantly different between methods (PF>MP>SA). PET regional measures were more accurate with multi-atlas methods than with SA method.

Conclusions

Multi-atlas methods outperform SA for automated anatomical brain segmentation and PET measure’s extraction. They perform comparably to manual segmentation for FDG-PET quantification. Multi-atlas methods are suitable for rapid reproducible VOI analyses.     

Development and Validation of Intracranial Thrombus Segmentation on CT Angiography in Patients with Acute Ischemic Stroke

Background and Purpose

Thrombus characterization is increasingly considered important in predicting treatment success for patients with acute ischemic stroke. The lack of intensity contrast between thrombus and surrounding tissue in CT images makes manual delineation a difficult and time consuming task. Our aim was to develop an automated method for thrombus measurement on CT angiography and validate it against manual delineation.

Materials and Methods

Automated thrombus segmentation was achieved using image intensity and a vascular shape prior derived from the segmentation of the contralateral artery. In 53 patients with acute ischemic stroke due to proximal intracranial arterial occlusion, automated length and volume measurements were performed. Accuracy was assessed by comparison with inter-observer variation of manual delineations using intraclass correlation coefficients and Bland–Altman analyses.

Results

The automated method successfully segmented the thrombus for all 53 patients. The intraclass correlation of automated and manual length and volume measurements were 0.89 and 0.84. Bland-Altman analyses yielded a bias (limits of agreement) of −0.4 (−8.8, 7.7) mm and 8 (−126, 141) mm³ for length and volume, respectively. This was comparable to the best interobserver agreement, with an intraclass correlation coefficients of 0.90 and 0.85 and a bias (limits of agreement) of −0.1 (−11.2, 10.9) mm and −17 (−216, 185) mm³.

Conclusions

The method facilitates automated thrombus segmentation for accurate length and volume measurements, is relatively fast and requires minimal user input, while being insensitive to high hematocrit levels and vascular calcifications. Furthermore, it has the potential to assess thrombus characteristics of low-density thrombi.     

Assessment of automated disease detection in diabetic retinopathy screening using two-field photography

Aim

To assess the performance of automated disease detection in diabetic retinopathy screening using two field mydriatic photography.

Methods

Images from 8,271 sequential patient screening episodes from a South London diabetic retinopathy screening service were processed by the Medalytix iGrading™ automated grading system. For each screening episode macular-centred and disc-centred images of both eyes were acquired and independently graded according to the English national grading scheme. Where discrepancies were found between the automated result and original manual grade, internal and external arbitration was used to determine the final study grades. Two versions of the software were used: one that detected microaneurysms alone, and one that detected blot haemorrhages and exudates in addition to microaneurysms. Results for each version were calculated once using both fields and once using the macula-centred field alone.

Results

Of the 8,271 episodes, 346 (4.2%) were considered unassessable. Referable disease was detected in 587 episodes (7.1%). The sensitivity of the automated system for detecting unassessable images ranged from 97.4% to 99.1% depending on configuration. The sensitivity of the automated system for referable episodes ranged from 98.3% to 99.3%. All the episodes that included proliferative or pre-proliferative retinopathy were detected by the automated system regardless of configuration (192/192, 95% confidence interval 98.0% to 100%). If implemented as the first step in grading, the automated system would have reduced the manual grading effort by between 2,183 and 3,147 patient episodes (26.4% to 38.1%).

Conclusion

Automated grading can safely reduce the workload of manual grading using two field, mydriatic photography in a routine screening service.     

Design of DNA Pooling to Allow Incorporation of Covariates in Rare Variants Analysis

Background

Rapid advances in next-generation sequencing technologies facilitate genetic association studies of an increasingly wide array of rare variants. To capture the rare or less common variants, a large number of individuals will be needed. However, the cost of a large scale study using whole genome or exome sequencing is still high. DNA pooling can serve as a cost-effective approach, but with a potential limitation that the identity of individual genomes would be lost and therefore individual characteristics and environmental factors could not be adjusted in association analysis, which may result in power loss and a biased estimate of genetic effect.

Methods

For case-control studies, we propose a design strategy for pool creation and an analysis strategy that allows covariate adjustment, using multiple imputation technique.

Results

Simulations show that our approach can obtain reasonable estimate for genotypic effect with only slight loss of power compared to the much more expensive approach of sequencing individual genomes.

Conclusion

Our design and analysis strategies enable more powerful and cost-effective sequencing studies of complex diseases, while allowing incorporation of covariate adjustment.     

Increased Throughput by Parallelization of Library Preparation for Massive Sequencing

Background

Massively parallel sequencing systems continue to improve on data output, while leaving labor-intensive library preparations a potential bottleneck. Efforts are currently under way to relieve the crucial and time-consuming work to prepare DNA for high-throughput sequencing.

Methodology/Principal Findings

In this study, we demonstrate an automated parallel library preparation protocol using generic carboxylic acid-coated superparamagnetic beads and polyethylene glycol precipitation as a reproducible and flexible method for DNA fragment length separation. With this approach the library preparation for DNA sequencing can easily be adjusted to a desired fragment length. The automated protocol, here demonstrated using the GS FLX Titanium instrument, was compared to the standard manual library preparation, showing higher yield, throughput and great reproducibility. In addition, 12 libraries were prepared and uniquely tagged in parallel, and the distribution of sequence reads between these indexed samples could be improved using quantitative PCR-assisted pooling.

Conclusions/Significance

We present a novel automated procedure that makes it possible to prepare 36 indexed libraries per person and day, which can be increased to up to 96 libraries processed simultaneously. The yield, speed and robust performance of the protocol constitute a substantial improvement to present manual methods, without the need of extensive equipment investments. The described procedure enables a considerable efficiency increase for small to midsize sequencing centers.     

Identifying ontogenetic, environmental and individual components of forest tree growth

Background and Aims

This study aimed to identify and characterize the ontogenetic, environmental and individual components of forest tree growth. In the proposed approach, the tree growth data typically correspond to the retrospective measurement of annual shoot characteristics (e.g. length) along the trunk.

Methods

Dedicated statistical models (semi-Markov switching linear mixed models) were applied to data sets of Corsican pine and sessile oak. In the semi-Markov switching linear mixed models estimated from these data sets, the underlying semi-Markov chain represents both the succession of growth phases and their lengths, while the linear mixed models represent both the influence of climatic factors and the inter-individual heterogeneity within each growth phase.

Key Results

On the basis of these integrative statistical models, it is shown that growth phases are not only defined by average growth level but also by growth fluctuation amplitudes in response to climatic factors and inter-individual heterogeneity and that the individual tree status within the population may change between phases. Species plasticity affected the response to climatic factors while tree origin, sampling strategy and silvicultural interventions impacted inter-individual heterogeneity.

Conclusions

The transposition of the proposed integrative statistical modelling approach to cambial growth in relation to climatic factors and the study of the relationship between apical growth and cambial growth constitute the next steps in this research.     

Variability of the QuantiFERON?-TB Gold In-Tube Test Using Automated and Manual Methods

Background

The QuantiFERON®-TB Gold In-Tube test (QFT-GIT) detects Mycobacterium tuberculosis (Mtb) infection by measuring release of interferon gamma (IFN-γ) when T-cells (in heparinized whole blood) are stimulated with specific Mtb antigens. The amount of IFN-γ is determined by enzyme-linked immunosorbent assay (ELISA). Automation of the ELISA method may reduce variability. To assess the impact of ELISA automation, we compared QFT-GIT results and variability when ELISAs were performed manually and with automation.

Methods

Blood was collected into two sets of QFT-GIT tubes and processed at the same time. For each set, IFN-γ was measured in automated and manual ELISAs. Variability in interpretations and IFN-γ measurements was assessed between automated (A1 vs. A2) and manual (M1 vs. M2) ELISAs. Variability in IFN-γ measurements was also assessed on separate groups stratified by the mean of the four ELISAs.

Results

Subjects (N = 146) had two automated and two manual ELISAs completed. Overall, interpretations were discordant for 16 (11%) subjects. Excluding one subject with indeterminate results, 7 (4.8%) subjects had discordant automated interpretations and 10 (6.9%) subjects had discordant manual interpretations (p = 0.17). Quantitative variability was not uniform; within-subject variability was greater with higher IFN-γ measurements and with manual ELISAs. For subjects with mean TB Responses ±0.25 IU/mL of the 0.35 IU/mL cutoff, the within-subject standard deviation for two manual tests was 0.27 (CI₉₅ = 0.22–0.37) IU/mL vs. 0.09 (CI₉₅ = 0.07–0.12) IU/mL for two automated tests.

Conclusion

QFT-GIT ELISA automation may reduce variability near the test cutoff. Methodological differences should be considered when interpreting and using IFN-γ release assays (IGRAs).     

Assessing the Goodness of Fit of Phylogenetic Comparative Methods: A Meta-Analysis and Simulation Study

Background

Phylogenetic comparative methods (PCMs) have been applied widely in analyzing data from related species but their fit to data is rarely assessed.

Question

Can one determine whether any particular comparative method is typically more appropriate than others by examining comparative data sets?

Data

I conducted a meta-analysis of 122 phylogenetic data sets found by searching all papers in JEB, Blackwell Synergy and JSTOR published in 2002–2005 for the purpose of assessing the fit of PCMs. The number of species in these data sets ranged from 9 to 117.

Analysis Method

I used the Akaike information criterion to compare PCMs, and then fit PCMs to bivariate data sets through REML analysis. Correlation estimates between two traits and bootstrapped confidence intervals of correlations from each model were also compared.

Conclusions

For phylogenies of less than one hundred taxa, the Independent Contrast method and the independent, non-phylogenetic models provide the best fit.For bivariate analysis, correlations from different PCMs are qualitatively similar so that actual correlations from real data seem to be robust to the PCM chosen for the analysis. Therefore, researchers might apply the PCM they believe best describes the evolutionary mechanisms underlying their data.     

Computer-Assisted Interpretation of the EEG Background Pattern: A Clinical Evaluation

Objective

Interpretation of the EEG background pattern in routine recordings is an important part of clinical reviews. We evaluated the feasibility of an automated analysis system to assist reviewers with evaluation of the general properties in the EEG background pattern.

Methods

Quantitative EEG methods were used to describe the following five background properties: posterior dominant rhythm frequency and reactivity, anterior-posterior gradients, presence of diffuse slow-wave activity and asymmetry. Software running the quantitative methods were given to ten experienced electroencephalographers together with 45 routine EEG recordings and computer-generated reports. Participants were asked to review the EEGs by visual analysis first, and afterwards to compare their findings with the generated reports and correct mistakes made by the system. Corrected reports were returned for comparison.

Results

Using a gold-standard derived from the consensus of reviewers, inter-rater agreement was calculated for all reviewers and for automated interpretation. Automated interpretation together with most participants showed high (kappa > 0.6) agreement with the gold standard. In some cases, automated analysis showed higher agreement with the gold standard than participants. When asked in a questionnaire after the study, all participants considered computer-assisted interpretation to be useful for every day use in routine reviews.

Conclusions

Automated interpretation methods proved to be accurate and were considered to be useful by all participants.

Significance

Computer-assisted interpretation of the EEG background pattern can bring consistency to reviewing and improve efficiency and inter-rater agreement.     

Potent Antiproliferative Cembrenoids Accumulate in Tobacco upon Infection with Rhodococcus fascians and Trigger Unusual Microtubule Dynamics in Human Glioblastoma Cells

Aims

Though plant metabolic changes are known to occur during interactions with bacteria, these were rarely challenged for pharmacologically active compounds suitable for further drug development. Here, the occurrence of specific chemicals with antiproliferative activity against human cancer cell lines was evidenced in hyperplasia (leafy galls) induced when plants interact with particular phytopathogens, such as the Actinomycete Rhodococcus fascians.

Methods

We examined leafy galls fraction F3.1.1 on cell proliferation, cell division and cytoskeletal disorganization of human cancer cell lines using time-lapse videomicroscopy imaging, combined with flow cytometry and immunofluorescence analysis. We determined the F3.1.1-fraction composition by gas chromatography coupled to mass spectrometry.

Results

The leafy galls induced on tobacco by R. fascians yielded fraction F3.1.1 which inhibited proliferation of glioblastoma U373 cells with an IC₅₀ of 4.5 µg/mL, F.3.1.1 was shown to increase cell division duration, cause nuclear morphological deformations and cell enlargement, and, at higher concentrations, karyokinesis defects leading to polyploidization and apoptosis. F3.1.1 consisted of a mixture of isomers belonging to the cembrenoids. The cellular defects induced by F3.1.1 were caused by a peculiar cytoskeletal disorganization, with the occurrence of fragmented tubulin and strongly organized microtubule aggregates within the same cell. Colchicine, paclitaxel, and cembrene also affected U373 cell proliferation and karyokinesis, but the induced microtubule rearrangement was very different from that provoked by F3.1.1. Altogether our data indicate that the cembrenoid isomers in F3.1.1 have a unique mode of action and are able to simultaneously modulate microtubule polymerization and stability.     

The assessment of post-vasectomy pain in mice using behaviour and the Mouse Grimace Scale

Background

Current behaviour-based pain assessments for laboratory rodents have significant limitations. Assessment of facial expression changes, as a novel means of pain scoring, may overcome some of these limitations. The Mouse Grimace Scale appears to offer a means of assessing post-operative pain in mice that is as effective as manual behavioural-based scoring, without the limitations of such schemes. Effective assessment of post-operative pain is not only critical for animal welfare, but also the validity of science using animal models.

Methodology/Principal Findings

This study compared changes in behaviour assessed using both an automated system (“HomeCageScan”) and using manual analysis with changes in facial expressions assessed using the Mouse Grimace Scale (MGS). Mice (n = 6/group) were assessed before and after surgery (scrotal approach vasectomy) and either received saline, meloxicam or bupivacaine. Both the MGS and manual scoring of pain behaviours identified clear differences between the pre and post surgery periods and between those animals receiving analgesia (20 mg/kg meloxicam or 5 mg/kg bupivacaine) or saline post-operatively. Both of these assessments were highly correlated with those showing high MGS scores also exhibiting high frequencies of pain behaviours. Automated behavioural analysis in contrast was only able to detect differences between the pre and post surgery periods.

Conclusions

In conclusion, both the Mouse Grimace Scale and manual scoring of pain behaviours are assessing the presence of post-surgical pain, whereas automated behavioural analysis could be detecting surgical stress and/or post-surgical pain. This study suggests that the Mouse Grimace Scale could prove to be a quick and easy means of assessing post-surgical pain, and the efficacy of analgesic treatment in mice that overcomes some of the limitations of behaviour-based assessment schemes.     

Circulating Tumor Cells Count and Morphological Features in Breast,Colorectal and Prostate Cancer

Background

Presence of circulating tumor cells (CTC) in patients with metastatic breast, colorectal and prostate cancer is indicative for poor prognosis. An automated CTC (aCTC) algorithm developed previously to eliminate the variability in manual counting of CTC (mCTC) was used to extract morphological features. Here we validated the aCTC algorithm on CTC images from prostate, breast and colorectal cancer patients and investigated the role of quantitative morphological parameters.

Methodology

Stored images of samples from patients with prostate, breast and colorectal cancer, healthy controls, benign breast and colorectal tumors were obtained using the CellSearch system. Images were analyzed for the presence of aCTC and their morphological parameters measured and correlated with survival.

Results

Overall survival hazard ratio was not significantly different for aCTC and mCTC. The number of CTC correlated strongest with survival, whereas CTC size, roundness and apoptosis features reached significance in univariate analysis, but not in multivariate analysis. One aCTC/7.5 ml of blood was found in 7 of 204 healthy controls and 9 of 694 benign tumors. In one patient with benign tumor 2 and another 9 aCTC were detected.

Significance of the study

CTC can be identified and morphological features extracted by an algorithm on images stored by the CellSearch system and strongly correlate with clinical outcome in metastatic breast, colorectal and prostate cancer.     

Relationship between Orthostatic Hypotension and White Matter Hyperintensity Load in Older Patients with Mild Dementia

Background/Objectives

White matter hyperintensities (WMH) in magnetic resonance imaging (MRI) scans of the brain, and orthostatic hypotension (OH) are both common in older people. We tested the hypothesis that OH is associated with WMH.

Design

Cross-sectional study.

Setting

Secondary care outpatient clinics in geriatric medicine and old age psychiatry in western Norway.

Participants

160 older patients with mild dementia, diagnosed according to standardised criteria.

Measurements

OH was diagnosed according to the consensus definition, measuring blood pressure (BP) in the supine position and within 3 minutes in the standing position. MRI scans were performed according to a common protocol at three centres, and the volumes of WMH were quantified using an automated method (n = 82), followed by manual editing. WMH were also quantified using the visual Scheltens scale (n = 139). Multiple logistic regression analyses were applied, with highest vs. lowest WMH quartile as response.

Results

There were no significant correlations between WMH volumes and systolic or diastolic orthostatic BP drops, and no significant correlations between Scheltens scores of WMH and systolic or diastolic BP drops. In the multivariate analyses, only APOEε4 status remained a significant predictor for WMH using the automated method (p = 0.037, OR 0.075 (0.007–0.851)), whereas only age remained a significant predictor for WMH scores (p = 0.019, OR 1.119 (1.018–1.230)).

Conclusion

We found no association between OH and WMH load in a sample of older patients with mild dementia.     

CDK11(p58) is required for centriole duplication and Plk4 recruitment to mitotic centrosomes

Background

CDK11^p58 is a mitotic protein kinase, which has been shown to be required for different mitotic events such as centrosome maturation, chromatid cohesion and cytokinesis.

Methodology/Principal Findings

In addition to these previously described roles, our study shows that CDK11^p58 inhibition induces a failure in the centriole duplication process in different human cell lines. We propose that this effect is mediated by the defective centrosomal recruitment of proteins at the onset of mitosis. Indeed, Plk4 protein kinase and the centrosomal protein Cep192, which are key components of the centriole duplication machinery, showed reduced levels at centrosomes of mitotic CDK11-depleted cells. CDK11^p58, which accumulates only in the vicinity of mitotic centrosomes, directly interacts with the centriole-associated protein kinase Plk4 that regulates centriole number in cells. In addition, we show that centriole from CDK11 defective cells are not able to be over duplicated following Plk4 overexpression.

Conclusion/Significance

We thus propose that CDK11 is required for centriole duplication by two non-mutually-exclusive mechanisms. On one hand, the observed duplication defect could be caused indirectly by a failure of the centrosome to fully maturate during mitosis. On the other hand, CDK11^p58 could also directly regulate key centriole components such as Plk4 during mitosis to trigger essential mitotic centriole modifications, required for centriole duplication during subsequent interphase.     

The distribution and mutagenesis of short coding INDELs from 1,128 whole exomes

Background

Identifying insertion/deletion polymorphisms (INDELs) with high confidence has been intrinsically challenging in short-read sequencing data. Here we report our approach for improving INDEL calling accuracy by using a machine learning algorithm to combine call sets generated with three independent methods, and by leveraging the strengths of each individual pipeline. Utilizing this approach, we generated a consensus exome INDEL call set from a large dataset generated by the 1000 Genomes Project (1000G), maximizing both the sensitivity and the specificity of the calls.

Results

This consensus exome INDEL call set features 7,210 INDELs, from 1,128 individuals across 13 populations included in the 1000 Genomes Phase 1 dataset, with a false discovery rate (FDR) of about 7.0%.

Conclusions

In our study we further characterize the patterns and distributions of these exonic INDELs with respect to density, allele length, and site frequency spectrum, as well as the potential mutagenic mechanisms of coding INDELs in humans.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1333-7) contains supplementary material, which is available to authorized users.