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  • 1
    In: mSystems, American Society for Microbiology, Vol. 8, No. 3 ( 2023-06-29)
    Abstract: With the currently available antibiotics, the treatment of TB takes months. The slow response to treatment is caused by antibiotic tolerance, which is especially common among bacteria that form biofilms. Such biofilms are composed of bacterial cells surrounded by the extracellular matrix. Both the matrix and the dormant lifestyle of the bacterial cells are thought to hinder the efficacy of antibiotics. To be able to develop faster-acting treatments against TB, the biofilm forms of mycobacteria deserve specific attention. In this work, we characterize the protein composition of Mmr biofilms in bacterial cultures and in mycobacteria extracted from infected adult zebrafish. We identify abundant surface-exposed targets and develop the first sybodies that bind to mycobacterial biofilms. As nanobodies can be linked to other therapeutic compounds, in the future, they can provide means to target therapies to biofilms.
    Type of Medium: Online Resource
    ISSN: 2379-5077
    Language: English
    Publisher: American Society for Microbiology
    Publication Date: 2023
    detail.hit.zdb_id: 2844333-0
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  • 2
    Online Resource
    Online Resource
    Wiley ; 2020
    In:  Methods in Ecology and Evolution Vol. 11, No. 2 ( 2020-02), p. 333-344
    In: Methods in Ecology and Evolution, Wiley, Vol. 11, No. 2 ( 2020-02), p. 333-344
    Abstract: Dispersal, the movement of individuals between populations, is crucial in many ecological and genetic processes. However, direct identification of dispersing individuals is difficult or impossible in natural populations. By using genetic assignment methods, individuals with unknown genetic origin can be assigned to source populations. This knowledge is necessary in studying many key questions in ecology, evolution and conservation. We introduce a network‐based tool BONE (Baseline Oriented Network Estimation) for genetic population assignment, which borrows concepts from undirected graph inference. In particular, we use sparse multinomial Least Absolute Shrinkage and Selection Operator (LASSO) regression to estimate probability of the origin of all mixture individuals and their mixture proportions without tedious selection of the LASSO tuning parameter. We compare BONE with three genetic assignment methods implemented in R packages radmixture , assignPOP and RUBIAS . Probability of the origin and mixture proportion estimates of both simulated and real data (an insular house sparrow metapopulation and Chinook salmon populations) given by BONE are competitive or superior compared to other assignment methods. Our examples illustrate how the network estimation method adapts to population assignment, combining the efficiency and attractive properties of sparse network representation and model selection properties of the L 1 regularization. As far as we know, this is the first approach showing how one can use network tools for genetic identification of individuals' source populations. BONE is aimed at any researcher performing genetic assignment and trying to infer the genetic population structure. Compared to other methods, our approach also identifies outlying mixture individuals that could originate outside of the baseline populations. BONE is a freely available R package under the GPL licence and can be downloaded at GitHub. In addition to the R package, a tutorial for BONE is available at https://github.com/markkukuismin/BONE/ .
    Type of Medium: Online Resource
    ISSN: 2041-210X , 2041-210X
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 2528492-7
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  • 3
    In: Molecular Ecology, Wiley, Vol. 30, No. 19 ( 2021-10), p. 4740-4756
    Abstract: Dispersal has a crucial role determining ecoevolutionary dynamics through both gene flow and population size regulation. However, to study dispersal and its consequences, one must distinguish immigrants from residents. Dispersers can be identified using telemetry, capture‐mark‐recapture (CMR) methods, or genetic assignment methods. All of these methods have disadvantages, such as high costs and substantial field efforts needed for telemetry and CMR surveys, and adequate genetic distance required in genetic assignment. In this study, we used genome‐wide 200K Single Nucleotide Polymorphism data and two different genetic assignment approaches (GSI_SIM, Bayesian framework; BONE, network‐based estimation) to identify the dispersers in a house sparrow ( Passer domesticus ) metapopulation sampled over 16 years. Our results showed higher assignment accuracy with BONE. Hence, we proceeded to diagnose potential sources of errors in the assignment results from the BONE method due to variation in levels of interpopulation genetic differentiation, intrapopulation genetic variation and sample size. We show that assignment accuracy is high even at low levels of genetic differentiation and that it increases with the proportion of a population that has been sampled. Finally, we highlight that dispersal studies integrating both ecological and genetic data provide robust assessments of the dispersal patterns in natural populations.
    Type of Medium: Online Resource
    ISSN: 0962-1083 , 1365-294X
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 2020749-9
    detail.hit.zdb_id: 1126687-9
    SSG: 12
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