In vitro and ex vivo proteomics of Mycobacterium marinum biofilms and the development of biofilm-binding synthetic nanobodies

The antibiotic-tolerant biofilms present in tuberculous granulomas add an additional layer of complexity when treating mycobacterial infections, including tuberculosis (TB). For a more efficient treatment of TB, the biofilm forms of mycobacteria warrant specific attention. Here, we used Mycobacterium marinum (Mmr) as a biofilm-forming model to identify the abundant proteins covering the biofilm surface. We used biotinylation/streptavidin-based proteomics on the proteins exposed at the Mmr biofilm matrices in vitro to identify 448 proteins and ex vivo proteomics to detect 91 Mmr proteins from the mycobacterial granulomas isolated from adult zebrafish. In vitro and ex vivo proteomics data are available via ProteomeXchange with identifiers PXD033425 and PXD039416, respectively. Data comparisons pinpointed the molecular chaperone GroEL2 as the most abundant Mmr protein within the in vitro and ex vivo proteomes, while its paralog, GroEL1, with a known role in biofilm formation, was detected with slightly lower intensity values. To validate the surface exposure of these targets, we created in-house synthetic nanobodies (sybodies) against the two chaperones and identified sybodies that bind the mycobacterial biofilms in vitro and those present in ex vivo granulomas. Taken together, the present study reports a proof-of-concept showing that surface proteomics in vitro and ex vivo proteomics combined is a valuable strategy to identify surface-exposed proteins on the mycobacterial biofilm. Biofilm surface–binding nanobodies could be eventually used as homing agents to deliver biofilm-targeting treatments to the sites of persistent biofilm infection.Peer reviewe

A search for spectral hysteresis and energy-dependent time lags from X-ray and TeV gamma-ray observations of Mrk 421

Blazars are variable emitters across all wavelengths over a wide range of timescales, from months down to minutes. It is therefore essential to observe blazars simultaneously at different wavelengths, especially in the X-ray and gamma-ray bands, where the broadband spectral energy distributions usually peak. In this work, we report on three "target-of-opportunity" (ToO) observations of Mrk 421, one of the brightest TeV blazars, triggered by a strong flaring event at TeV energies in 2014. These observations feature long, continuous, and simultaneous exposures with XMM-Newton (covering X-ray and optical/ultraviolet bands) and VERITAS (covering TeV gamma-ray band), along with contemporaneous observations from other gamma-ray facilities (MAGIC and Fermi-LAT) and a number of radio and optical facilities. Although neither rapid flares nor significant X-ray/TeV correlation are detected, these observations reveal subtle changes in the X-ray spectrum of the source over the course of a few days. We search the simultaneous X-ray and TeV data for spectral hysteresis patterns and time delays, which could provide insight into the emission mechanisms and the source properties (e.g. the radius of the emitting region, the strength of the magnetic field, and related timescales). The observed broadband spectra are consistent with a one-zone synchrotron self-Compton model. We find that the power spectral density distribution at $\gtrsim 4\times 10^{-4}$ Hz from the X-ray data can be described by a power-law model with an index value between 1.2 and 1.8, and do not find evidence for a steepening of the power spectral index (often associated with a characteristic length scale) compared to the previously reported values at lower frequencies.Comment: 45 pages, 15 figure

Mykobakteerin aiheuttamien granuloomien histologinen karakterisointi mutatoidussa seeprakalassa

Tuberkuloosi on edelleen yksi vaarallisimmista infektiotaudeista maailmassa ja aiheuttaa noin 1.5 miljoonaa kuolemaan vuosittain. Maailman terveysjärjestön (WHO) arvion mukaan neljäsosa maailman väestöstä kantaa Mycobacterium tuberculosis -bakteeria. Nykyisissä hoitomenetelmissä tuberkuloosia vastaan on puutteita ja ainoa käytössä oleva tuberkuloosirokote ei tarjoa riittävää suojaa tautia vastaan, minkä vuoksi uusille lääkkeille ja rokotteille on huomattava tarve. Hyviä eläinmalleja tuberkuloositutkimukselle on ollut puutteellisesti saatavilla, mutta lähivuosina seeprakalan (Danio rerio) on havaittu olevan hyvä mallieläin etenkin tutkittaessa granuloomien muodostumista, latenssia sekä taudin reaktivaatiota. Seeprakalan luonnollinen taudinaiheuttaja, Mycobacterium marinum, aiheuttaa samankaltaisen taudin kalassa kuin M. tuberculosis ihmisessä. Yksi tuberkuloosin ominaisuuksista on granuloomien muodostuminen. Granuloomat ovat immuunisoluaggregaatteja, joiden sisälle bakteerit ovat suljettuina. M. tuberculosis kykenee kuitenkin pakenemaan granuloomasta ja leviämään isännän elimistöön. Inflammasomi on immuunijärjestelmän mekanismi, joka osallistuu immuunijärjestelmän aktivaatioon infektiossa sekä granuloomien mudostumiseen. PYCARD on adaptoriproteiini, jolla on rooli inflammasomin aktivaatiossa, mikä tekee siitä mielenkiintoisen kohteen tutkittaessa immuunivastetta M. tuberculosis -infektiossa. Tässä tutkimuksessa vertailtiin granuloomien muodostumista pycard-/- ja pycard+/+ seeprakaloissa. Granuloomien kokoa, sijaintia, rakennetta sekä hypoksisuutta tarkasteltiin ja granuloomien kokonaismäärä sekä vapaan bakteerin määrä kaloissa laskettiin. Huomattavia eroja pycard-/- ja pycard+/+ seeprakalojen välillä ei havaittu minkään tarkastellun ominaisuuden kohdalla. Granuloomissa oli merkittävää vaihtelua kalayksilöiden välillä molemmissa ryhmissä.Tuberculosis (TB) still ranks as one of the most dangerous infectious diseases around the world and it is accountable for over 1.5 million deaths every year. World Health Organization has estimated that one fourth of the world’s population is infected with Mycobacterium tuberculosis. The current treatment against TB has drawbacks and the only available vaccine against TB does not provide sufficient protection against the disease and therefore new treatments are much needed. There has also been a lack of good animal models, but the zebrafish (Danio rerio) have been recently found to be a good model to study especially granuloma formation, latency, and reactivation of TB. Their natural pathogen, Mycobacterium marinum causes similar infection in the fish than M. tuberculosis in humans. One characteristic of TB is the formation of granulomas, which are aggregates of immune cells that contain the bacteria. However, M. tuberculosis can escape the granuloma and in such a way spread in the host. The inflammasome is an innate immune system mechanism that activates the immunological response in an infection and has a role in the formation of granulomas. PYCARD is an adaptor protein that has a role in inflammasome activation, which makes it an interesting target when studying the immunological response against M. tuberculosis infection. In this study, granuloma formation in pycard-/- and pycard+/+ zebrafish were compared. The granulomas were studied for their size, location, structure and hypoxicity, and the number of granulomas in each fish was counted. Also, the number of free bacteria was assessed. No significant differences were found in any of these aspects between pycard-/- and pycard+/+ fish. Variation between individual fish was great in both groups

Tuen tarpeen arviointi ja tukitoimien toteuttaminen kaksivuotisessa esiopetuskokeilussa : Varhaiskasvatuksen erityisopettajien ajatuksia

Tämän tutkimuksen tarkoituksena on selvittää varhaiskasvatuksen erityisopettajien näkemyksiä tuen tarpeisten lasten tuen tarpeen arviointiin ja tukitoimiin liittyen syksyllä 2021 alkaneessa kaksivuotisessa esiopetuskokeilussa. Pyrkimyksenä on selvittää, millainen asema tuen tarpeisilla lapsilla on uudessa kaksivuotisessa esiopetuksessa ja millaisin perustein lasten tuen tarvetta arvioidaan kaksivuotisessa esiopetuskokeilussa sekä millaisin keinoin tarvittavia tukitoimia toteutetaan. Tavoitteena oli myös selvittä, toteutuuko kaksivuotiselle esiopetuskokeilulle asetetut tavoitteet tuen tarpeisten lasten kohdalla. Aineisto koostui viidestä kokeiluun osallistuvien varhaiskasvatuksen erityisopettajien haastattelusta. Haastatteluista neljä toteutettiin etänä Teams-sovelluksen kautta ja yksi toteutettiin haastateltavan toiveesta lähihaastatteluna hänen toimipisteessään. Kerätty aineisto litteroitiin, värikoodattiin ja teemoiteltiin teoriaohjaavasti. Tutkimuksen tulokset osoittivat, että kaksivuotiselle esiopetuskokeilulle asetetut tuen tarpeisia lapsia koskevat tavoitteet toteutuivat pääsääntöisesti hyvin. Kaksivuotisen esiopetuskokeilun koettiin osaltaan edesauttavan tärkeän varhaisen tuen aloittamista. Kokeilun nähtiin myös tasa-arvoistavan kasvatusta ja opetusta inkluusion periaatteiden mukaisesti. Tärkeimpänä positiivisena asiana kokeilussa nähtiin aika, jota on saatu lisää kaksivuotisen esiopetuksen myötä. Yhdessä lisävuodessa pystytään tukemaan lapsentahtisuutta ja yksilön kehitystä entistä paremmin. Vaikka kaksivuotinen esiopetuskokeilu nähtiin pääasiassa positiivisena, heräsi haastatteluissa myös muutamia huolenaiheita kokeilun onnistumiseen liittyen. Resurssien puute vaikuttaa myös kaksivuotiseen esiopetukseen ja sen laadukkaaseen toteutukseen, varsinkin tuen tarpeisten lasten tukitoimissa. Myös epätietoisuus kaksivuotisen esiopetuksen ensimmäisen ja toisen vuoden jatkumosta herätti epäilyksiä. Kokeilussa on nähtävissä myös se, että esiopetusryhmän rakenne vaikuttaa suuresti kokeilulle asetettujen tavoitteiden toteutumiseen

Genetic assignment of individuals to source populations using network estimation tools

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 L1 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/

Genetic assignment of individuals to source populations using network estimation tools

Abstract 1. 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. 2. 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. 3. 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 L₁ 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. 4. 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/

In vitro and ex vivo proteomics of Mycobacterium marinum biofilms and the development of biofilm-binding synthetic nanobodies

The antibiotic-tolerant biofilms present in tuberculous granulomas add an additional layer of complexity when treating mycobacterial infections, including tuberculosis (TB). For a more efficient treatment of TB, the biofilm forms of mycobacteria warrant specific attention. Here, we used Mycobacterium marinum (Mmr) as a biofilm-forming model to identify the abundant proteins covering the biofilm surface. We used biotinylation/streptavidin-based proteomics on the proteins exposed at the Mmr biofilm matrices in vitro to identify 448 proteins and ex vivo proteomics to detect 91 Mmr proteins from the mycobacterial granulomas isolated from adult zebrafish. In vitro and ex vivo proteomics data are available via ProteomeXchange with identifier PXD033425 and PXD039416, respectively. Data comparisons pinpointed the molecular chaperone GroEL2 as the most abundant Mmr protein within the in vitro and ex vivo proteomes, while its paralog, GroEL1, with a known role in biofilm formation, was detected with slightly lower intensity values. To validate the surface exposure of these targets, we created in-house synthetic nanobodies (sybodies) against the two chaperones and identified sybodies that bind the mycobacterial biofilms in vitro and those present in ex vivo granulomas. Taken together, the present study reports a proof-of-concept showing that surface proteomics in vitro and ex vivo proteomics combined are a valuable strategy to identify surface-exposed proteins on the mycobacterial biofilm. Biofilm-surface-binding nanobodies could be eventually used as homing agents to deliver biofilm-targeting treatments to the sites of persistent biofilm infection.With the currently available antibiotics, the treatment of tuberculosis takes months. The slow response to treatment is caused by antibiotic tolerance, which is especially common among bacteria that forms 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 tuberculosis, the biofilm forms of mycobacteria deserve specific attention. In this work, we characterise the protein composition of Mycobacterium marinum biofilms in bacterial cultures and in mycobacteria extracted from infected adult zebrafish. We identify abundant surface-exposed targets and develop the first synthetic nanobodies 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.Peer reviewe

Dispersal in a house sparrow metapopulation: An integrative case study of genetic assignment calibrated with ecological data and pedigree information

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

Dispersal in a house sparrow metapopulation : An integrative case study of genetic assignment calibrated with ecological data and pedigree information

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