Biology subjects

Kaiser, M.

Publications and source records attributed to Kaiser, M..

65 records · Page 4Linked to original sources

bioRxiv2020

Creative destruction: a basic computational model of cortical layer formation

One of the most characteristic properties of many vertebrate neural systems is the layered organization of different cell types. This cytoarchitecture exists in the cortex, the retina, the hippocampus and many other parts of the central nervous system. The developmental mechanisms of neural layer formation have been subject to substantial experimental efforts. Here, we provide a general computational model for cortical layer formation in 3D physical space. We show that this multi-scale, agent-based model comprising two distinct stages of apoptosis, can account for the wide range of neuronal numbers encountered in different cortical areas and species. Our results demonstrate the phenotypic richness of a basic state diagram structure, and suggest a novel function for apoptosis. Moreover, slightly changed gene regulatory dynamics recapitulate characteristic properties observed in neurodevelopmental diseases. Overall, we propose a novel computational model using gene-type rules, exhibiting many characteristics of normal and pathological cortical development.

developmental biology↗

bioRxiv2020

Non-invasive monitoring of drug action: a new live in vitro assay design for Chagas' disease drug discovery

New assay designs are needed to improve the predictive value of the Trypanosoma cruzi in vitro tests used as part of the Chagas disease drug development pipeline. Here, we employed a green fluorescent protein (eGFP)-expressing parasite line and live high-content imaging to monitor the growth of T. cruzi amastigotes in mouse embryonic fibroblasts. A novel assay design allowed us to follow parasite numbers over 6 days, in four-hour intervals, while occupying the microscope for only 24 hours per biological replicate. Dose-response curves were calculated for each time point after addition of test compounds, revealing how EC50 values first decreased over the time of drug exposure, and then leveled off. However, we observed that parasite numbers could vary, even in the untreated controls, and at different sites in the same well, which caused variability in the EC50 values. To overcome this, we established that fold change in parasite number per hour is a more robust and informative measure of drug activity. This was calculated based on an exponential growth model for every biological sample. The net fold change per hour is the result of parasite replication, differentiation, and death. The calculation of this fold change enabled us to determine the tipping point of drug action, i.e. the point immediately before the fold change becomes negative, independent of the drug concentration and exposure time. This time-to-kill over drug concentration revealed specific pharmacodynamic profiles of the benchmark drugs benznidazole and posaconazole. Author SummaryChagas disease, caused by Trypanosoma cruzi, is a chronic debilitating infection occurring mostly in Latin America. There is an urgent need for new, well tolerated drugs. However, the latest therapeutic candidates have yielded disappointing outcomes in clinical trials, despite promising preclinical results. This demands new and more predictive in vitro assays. To address this, we have developed an assay design that enables the growth of T. cruzi intracellular forms to be monitored in real time, under drug pressure, for 6 days post-infection. This allowed us to establish the tipping point of drug action, when the parasites stop multiplying and start to die. The resulting pharmacodynamics profiles can provide robust and informative details on anti-chagasic candidates, as demonstrated for the benchmark drugs benznidazole and posaconazole.

microbiology↗

bioRxiv2019

Correcting reference bias from the Illumina Isaac aligner enables analysis of cancer genomes

Estimating the fraction of cancer cells with individual somatic mutations is central to many analyses in cancer genomics, including characterisation of clonal architecture and timing of mutational events. Estimation of these cancer cell fractions (CCFs) is contingent on unbiased assessment of the fraction of reads supporting variant alleles (VAFs). We demonstrate that VAFs computed by the Illumina Isaac pipeline, used in many large-scale sequencing projects including The 100,000 Genomes Project, are biased by the preferential soft clipping of reads supporting non-reference alleles (semi-aligned reads). We show that these biased VAFs can have deleterious effects on downstream analyses reliant on unbiased CCF estimates. While Isaac bias can be corrected through realignment with alternative parameters, this is computationally intensive. We therefore developed FixVAF, a tool for removing bias introduced by soft clipping of semi-aligned reads, facilitating downstream analyses without the need for realignment. FixVAF is freely available at https://github.com/danchubb/FixVAF.\n\nContactalex.cornish@icr.ac.uk or daniel.chubb@icr.ac.uk.

bioinformatics↗

bioRxiv2019

NIHBA: A Network Interdiction Approach with Hybrid Benders Algorithm for Strain Design

Flux balance analysis (FBA) based bilevel optimisation has been a great success in redesigning metabolic networks for biochemical overproduction. To date, many computational approaches have been developed to solve the resulting bilevel optimisation problems. However, most of them are of limited use due to biased optimality principle, poor scalability with the size of metabolic networks, potential numeric issues, or low quantity of design solutions in a single run. In this work, we have employed a network interdiction model free of growth optimality assumptions, a special case of bilevel optimisation, for computational strain design and have developed a hybrid Benders algorithm (HBA) that deals with complicating binary variables in the model, thereby achieving high efficiency without numeric issues in search of best design strategies. More importantly, HBA can list solutions that meet users production requirements during the search, making it possible to obtain numerous design strategies at a small runtime overhead (typically[~] 1 hour).

bioengineering↗

bioRxiv2019

Computational modelling of the long-term effects of brain stimulation on the local and global structural connectivity of epileptic patients

In patients with drug resistant focal epilepsy, targeted weak stimulation of the affected brain regions has been proposed as an alternative to surgery. However, the effectiveness of stimulation as a treatment presents great variation from patient to patient. In this study, brain activity is simulated for a period of one day using a network of Wilson-Cowan oscillators coupled according to diffusion imaging based structural connectivity. We use this computational model to examine the potential long-term effects of stimulation on brain connectivity. Our findings indicate that the overall simulated effect of stimulation is heavily dependent on the excitability of the stimulated regions. Additionally, stimulation seems to lead to long-term effects in the connectivity of secondary (non-stimulated) regions in epileptic patients. These effects are correlated with a worse surgery outcome in some patients, which suggests that long-term simulations could be used as a tool to determine suitability for surgery/stimulation.

neuroscience↗

bioRxiv2019

Targeting the trypanosome kinetochore with CLK1 protein kinase inhibitors

The kinetochore is a macromolecular structure that assembles on the centromeres of chromosomes and provides the major attachment point for spindle microtubules during mitosis. In Trypanosoma brucei the proteins that make up the kinetochore are highly divergent, with the inner kinetochore comprising at least 20 distinct and essential proteins (KKT1-20) that include four protein kinases, CLK1 (KKT10), CLK2 (KKT19), KKT2 and KKT3. We performed a phenotypic screen of T. brucei bloodstream forms with a Novartis kinase-focused inhibitor library, which identified a number of selective inhibitors with potent pan-kinetoplastid activity. Deconvolution of an amidobenzimidazole series using a selection of 37 T. brucei mutants that over-express known essential protein kinases identified CLK1 as the primary target. Biochemical studies show that the irreversible competitive inhibition of CLK1 is dependent on a Michael acceptor forming an irreversible bond with C215 in the ATP binding pocket, a residue that is not present in human CLK1, thereby providing selectivity. Chemical inhibition of CLK1 impairs inner kinetochore recruitment and compromises cell cycle progression, leading to cell death. We show that KKT2 is a substrate for CLK1 and identify phosphorylation of S508 to be essential for KKT2 function and for kinetochore assembly. We propose that CLK1 is part of a novel signalling cascade that controls kinetochore function via phosphorylation of the inner kinetochore protein kinase KKT2. This work highlights a novel drug target for trypanosomatid parasitic protozoa and a new chemical tool for investigating the function of their divergent kinetochores.

microbiology↗

bioRxiv2019

retroLEAP: rAAV-based retrograde trans-synaptic labeling, expression and perturbation

Identifying and manipulating synaptically connected neurons across brain regions remains a core challenge in understanding complex nervous systems. RetroLEAP is a novel approach for retrograde trans-synaptic Labelling, Expression And Perturbation. GFP-dependent recombinase (Flp-DOG) detects trans-synaptic transfer of GFP-tetanus toxin heavy chain fusion protein (GFP-TTC) and activates expression of any gene of interest in synaptically connected cells. RetroLEAP overcomes existing limitations, is non-toxic, highly flexible, efficient, sensitive and easy to implement.

neuroscience↗

bioRxiv2018

The functional brain favours segregated modular connectivity at old age unless targeted by neurodegeneration

Brains modular connectivity gives this organ resilience and adaptability. The ageing process alters the human brain, leading to modifications to its organised modularity and these changes are further accentuated by neurodegeneration, leading to disorganisation. To understand this further, we analysed modular variability--heterogeneity of modules--and modular dissociation--detachment from segregated connectivity--in two ageing cohorts and a mixed cohort of neurodegenerative diseases. Our results revealed that the brain follows a universal pattern of modular variability that matches highly active and metacognitive brain regions: the association cortices. We also proved that in ageing the brain moves towards a modular segregated structure despite presenting with increased modular heterogeneity--modules in older adults are not only segregated but their shape and size are more variable than in young adults. In the presence of neurodegeneration, the brain maintains its segregated connectivity globally but not locally; the modular brain shows patterns of differentiated pathology.

neuroscience↗

bioRxiv2018

Re-annotated Nicotiana benthamiana gene models for enhanced proteomics and reverse genetics

Nicotiana benthamiana is an important model organism and representative of the Solanaceae (Nightshade) family. N. benthamiana has a complex ancient allopolyploid genome with 19 chromosomes, and an estimated genome size of 3.1Gb. Several draft assemblies of the N. benthamiana genome have been generated, however, many of the gene-models in these draft assemblies appear incorrect. Here we present a nearly non-redundant database of 42,855 improved N. benthamiana gene-models. With an estimated 97.6% completeness, the new predicted proteome is more complete than the previous proteomes. We show that the database is more sensitive and accurate in proteomics applications, while maintaining a reasonable low gene number. As a proof-of-concept we use this proteome to compare the leaf extracellular (apoplastic) proteome to a total extract of leaves. Several gene families are more abundant in the apoplast. For one of these apoplastic protein families, the subtilases, we present a phylogenetic analysis illustrating the utility of this database. Besides proteome annotation, this database will aid the research community with improved target gene selection for genome editing and off-target prediction for gene silencing.

plant biology↗

bioRxiv2018

Dynamic functional connectivity changes in dementia with Lewy bodies and Alzheimer’s disease

We studied the dynamic functional connectivity profile of dementia with Lewy bodies (DLB) and Alzheimers disease (AD) and the relationship between dynamic connectivity and the temporally transient symptoms of cognitive fluctuations and visual hallucinations in DLB.\n\nResting state fMRI data from 31 DLB, 29 AD, and 31 healthy control participants were analysed using dual regression to determine between-network functional connectivity. We used a sliding window approach followed by k-means clustering and dynamic network analyses to study dynamic functional connectivity changes associated with AD and DLB. Network measures that showed significant group differences were tested for correlations with clinical symptom severity.\n\nAD and DLB patients spent more time than controls in sparse connectivity configurations with absence of strong positive and negative connections and a relative isolation of motor networks from other networks. Additionally, DLB patients spent less time in a more strongly connected state and the variability of global brain network efficiency was reduced in DLB compared to controls. However, there were no significant correlations between dynamic connectivity measures and clinical scores.\n\nThe loss of global efficiency variability in DLB might indicate the presence of an abnormally rigid brain network and the lack of economical dynamics, factors which could contribute to an inability to respond appropriately to situational demands. However, the absence of significant clinical correlations indicates that the severity of transient cognitive symptoms such as cognitive fluctuations and visual hallucinations might not be directly related to these dynamic connectivity changes observed during a short resting state scan.

neuroscience↗

bioRxiv2017

KCC2-dependent Steady-state Intracellular Chloride Concentration and pH in Cortical Layer 2/3 Neurons of Anesthetized and Awake Mice

Neuronal intracellular Cl- concentration ([Cl-]i) influences a wide range of processes such as neuronal inhibition, membrane potential dynamics, intracellular pH (pHi) or cell volume. Up to date, neuronal [Cl-]i has predominantly been studied in model systems of reduced complexity. Here, we implemented the genetically encoded ratiometric Cl- indicator Superclomeleon (SCLM) to estimate the steady-state [Cl-]i in cortical neurons from anesthetized and awake mice using 2-photon microscopy. Additionally, we implemented superecliptic pHluorin as a ratiometric sensor to estimate the intracellular steady-state pH (pHi) of mouse cortical neurons in vivo. We estimated an average resting [Cl-]i of 6 {+/-} 2 mM with no evidence of subcellular gradients in the proximal somato-dendritic domain and an average somatic pHi of 7.1 {+/-} 0.1. Neither [Cl-]i nor pHi were affected by isoflurane anesthesia. We deleted the cation-Cl- co-transporter KCC2 in single identified neurons of adult mice and found an increase of [Cl-]i to approximately 26 {+/-} 8 mM, demonstrating that under in vivo conditions KCC2 produces low [Cl-]i in adult mouse neurons. In summary, neurons of the brain of awake adult mice exhibit a low and evenly distributed [Cl-]i in the proximal somato-dendritic compartment that is independent of anesthesia and requires KCC2 expression for its maintenance.

neuroscience↗