Merge pull request #971 from ScilifelabDataCentre/develop

Updates W16

content/english/dashboards/post_covid.md

@@ -81,6 +81,10 @@ The maps below show the number of people that received the diagnoses of interest
 
 **Code used to produce plot:** [Data preparation script](https://github.com/ScilifelabDataCentre/covid-portal-visualisations/blob/main/postCOVID/postcovid_dataprep.py), [Script to produce map](https://github.com/ScilifelabDataCentre/covid-portal-visualisations/blob/main/postCOVID/postcovid_mapfig_population_U089.py).
 
+<!--
+
+{{/* The data used for this is not available anymore, this section should be removed if no alternatives found */}}
+
 ### Geographic distribution of diagnosed cases relative to confirmed COVID-19 cases
 
 The maps below show the number of people that received the diagnoses of interest in each county as a percentage of the total number of confirmed COVID-19 cases in that county (based on [data from the Public Health Agency (Folkhälsomyndigheten)](https://www.folkhalsomyndigheten.se/smittskydd-beredskap/utbrott/aktuella-utbrott/covid-19/statistik-och-analyser/bekraftade-fall-i-sverige/)). Specifically, the cumulative number of COVID-19 cases in the county at the date given for the last update of the number of diagnoses of interest. Both the total number of confirmed COVID-19 cases and the number of people who received the diagnoses of interest can be seen by hovering the mouse above a particular county. Please note that the data visualised on this map should be interpreted with considerable caution for a few reasons. One reason for this is that the number of COVID-19 cases is likely underestimated; some cases of COVID-19 are asymptomatic, and not all symptomatic cases will have been confirmed and reported. The diagnoses related to *Post COVID-19 condition* were also introduced later than COVID-19, so not all cases of *Post COVID-19 condition* are likely to have received a formal diagnosis. Further, since *Post COVID-19 condition* may not be diagnosed for months following acute COVID-19 infection, some cases of *Post COVID-19 condition* may develop from the COVID-19 cases already reported.
@@ -101,6 +105,8 @@ The maps below show the number of people that received the diagnoses of interest
 
 **Code used to produce plot:** [Data preparation script](https://github.com/ScilifelabDataCentre/covid-portal-visualisations/blob/main/postCOVID/postcovid_dataprep.py), [Script to produce map](https://github.com/ScilifelabDataCentre/covid-portal-visualisations/blob/main/postCOVID/postcovid_mapfig_cases_U089.py).
 
+-->
+
 ### Most common accompanying diagnoses
 
 #### Diagnosis U09.9

content/english/highlights/antibiotic_resistance_development.md

@@ -0,0 +1,46 @@
+---
+title: New study shows that perserverance can be the reason for antibiotic resistance development
+date: 2023-04-18
+summary: A study from Elf lab at Uppsala University/SciLifeLab shows perseverance can be a reason for antibiotic resistance development in *E. coli*. Microscopy image data shared in SciLifeLab Data Repository.
+banner: /highlights/banners/antibiotic_resistance_development_small.jpg
+banner_large: /highlights/banners/antibiotic_resistance_development.jpg
+banner_caption: Artistic illustration of perseverance courtesy Elf lab / Johan Elf, Irmeli Barkefors
+highlights_topics: [Antibiotic resistance]
+announcement: "This data highlight was also [published on the SciLifeLab Data Platform](https://data.scilifelab.se/highlights/antibiotic_resistance_development/), as the work described in this highlight constitutes data-driven life science. The Platform is a hub for data-driven life science in Sweden, containing multiple relevant resources, tools, and services. It includes information on multiple subjects, including infectious diseases, please check out the [Data Platform](https://data.scilifelab.se/) for more."
+---
+
+Antibiotics were introduced in the 1930s and have since revolutionised modern medicine and healthcare. However, over the last few decades, antimicrobial resistance has started to pose a serious threat to global healthcare, animal husbandry, and the agricultural industry. Antimicrobial resistance means that bacteria and other microbes develop the ability to survive and grow in the presence of antibiotic drugs. In 2019, [almost 1.3 million deaths were directly connected to antimicrobial resistance worldwide](https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(21)02724-0/fulltext#%20), and about 3 million resistant infections in the US alone. In Sweden, the corresponding number is about 10,000. Antimicrobial resistance is often referred to as a silent, or long-term pandemic. Decreased resistance development is central to future pandemic preparedness efforts, as we may enter an era where preventable disease can no longer be easily treated.
+
+To study resistance development, it is possible to use either above-MIC (minimal inhibitory concentration) or sub-MIC concentrations of antibiotics. A bacterial population cannot grow at or above-MIC conditions; if no pre-existing mutations or resistance elements are present, all cells in the population will eventually die. In sub-MIC selection conditions, the bacteria can grow, albeit poorly, and cells that acquire *de novo* resistance mutations will have a selective advantage. Most studies of antibiotic resistance development are performed in batch cultures with large populations. This means that most studies overlook cell-to-cell heterogeneity in the response to antibiotic exposure. Additional studies into the heterogeneity in cellular responses to antibiotics and how these responses connect to antimicrobial resistance development are therefore warranted.
+
+In a recently published article in PNAS, researchers from Science for Life Laboratory (SciLifeLab) and Uppsala University (First author: Gerrit Brandis; Corresponding authors: Gerrit Brandis, and Johan Elf) measured cell-to-cell heterogeneity in growth response as a function of antibiotic concentration, as well as how heterogeneity in antibiotic response affects antibiotic resistance development.
+
+Brandis, Larsson, and Elf systematically exposed *Escherichia coli* to sub-MIC and above-MIC concentrations of nine antibiotics from a number of different antibiotic classes. They analysed the bacterial growth response on the single-cell level, using time-lapse microscopy. The results showed that the cell-to-cell heterogeneity, measured as the coefficient of variation of the growth rates of the cells, increased as a function of concentration and exposure time for all nine antibiotics studied. For three antibiotics (carbenicillin, ceftriaxone, and gentamycin), the difference in growth increased more than what was expected from simple growth rate reduction. In addition, in the presence of rifampicin and nitrofurantoin, sub-populations of bacteria continued to grow at above-MIC antibiotic concentrations for up to 10 generations. The researchers defined antibiotic perseverance as the ability of a subpopulation to maintain replication longer than the main population even at the MIC. They also found that the presence of antibiotic perseverance increased the risk of antibiotic resistance development by up to 40-fold in gram-negative and gram-positive species.
+
+<figure class="figure float-end mx-2 w-50">
+<img src="/highlights/banners/antibiotic_resistance_development_graph.jpg" alt="{{ .Title }} " class="img-news-banner img-thumbnail">
+<figcaption class="figure-caption mt-1"><i>Figure 1 from Brandis et al. (2023), Overview of antibiotic exposure experiment.</i></figcaption>
+</figure>
+
+Previous research has indicated that heteroresistance, a phenomenon where parts of the population can sustain growth above MIC, and persistence (the ability to tolerate higher dosages of antibiotics by entering a dormant state) are factors that contribute to the development of antibiotic resistance. However, the bacteria identified in this study are not resistant; their ability to grow in the presence of the drug is likely due to chance. But with each cell division, there’s a risk that a resistance mutation might occur.  This is one of the rationales behind the recommendation to adhere strictly to antibiotic prescriptions and not terminate the treatment prematurely.
+
+>"This is a new concept that we call antibiotic perseverance," explains Gerrit Brandis, a researcher in the group. "Perseverance describes how a small group of bacteria capable of sustaining growth can accumulate mutations after being exposed to antibiotics. If they are lucky, and the patient unlucky, one of these mutations will allow them to tolerate the antibiotic.”
+
+In summary, studies of bacteria on the single-cell level have revealed new information about a small sub-population of bacteria that survives in the presence of antibiotic concentrations that would normally kill them. Brandis, Larsson and Elf concluded that so called antibiotic perseverance is a common phenomenon and that it may also potentially have effect on the development of antibiotic resistance across pathogenic bacteria.
+
+#### Data
+
+* Raw microscopy image data and computational code used for analysis and plotting have been deposited [here](https://doi.org/10.17044/scilifelab.21517710).
+* Supporting information is also available in the full text version of the [article](https://doi.org/10.1073/pnas.2216216120)
+
+#### Article
+
+DOI: [10.1073/pnas.2216216120](https://doi.org/10.1073/pnas.2216216120)
+
+Brandis, G., Larsson, J., & Elf, J. (2023). Antibiotic perseverance increases the risk of resistance development. In Proceedings of the National Academy of Sciences (Vol. 120, Issue 2). Proceedings of the National Academy of Sciences.
+
+#### Funding
+
+The study was funded by the European Council, The Swedish foundation for Strategic research, the Knut and Alice Wallenberg Foundation, and the eSSENCE initiative.
+
+Learn more about the Elf group here: <https://elflab.icm.uu.se>

content/english/resources-subprojects/bsl3-facility.md

@@ -4,7 +4,7 @@ category: "plp1"
 resource_info:
     name: "State-of-the-art biosafety level 3 (BSL3) facility"
     funded_project_title: "BSL3 Biomedicum-SciLifeLab Collaborative Platform"
-    pi: Antonio Rothfuchs, Marjo Puumalainen
+    pi: Antonio Rothfuchs, Marianna Tampere
     host_organisation: Karolinska Institute
     use: "A lot of pandemic preparedness research requires a dedicated facility to handle pathogens in a safe environment. BSL3 Biomedicum offers both a safe environment for pathogen handling as well as expertise for research projects."
     access: "Access to the BSL-3 facility is preceded by the fulfillment of entry requirements which encompass understanding the risks associated with the handling of the pathogens used in the facility and understanding how to perform experiments with the same in an orderly and safe manner. As a service the facility provides training to new users and experimental support. Enquiries about access to the facility should be made well in advance so that risk assessments, permits, procedures and training needs can be addressed. To enquire access to the facility, please fill in the [project request form](/resorces/bsl3-facility-project-request-form.pdf) and send it to [[email protected]](mailto:[email protected])."

content/english/resources-subprojects/bsl3-network.md

@@ -4,14 +4,14 @@ category: "plp1"
 resource_info:
     name: "Swedish biosafety level 3 (BSL3) network"
     funded_project_title: "BSL3 Biomedicum-SciLifeLab Collaborative Platform"
-    pi: Antonio Rothfuchs, Marjo Puumalainen
+    pi: Antonio Rothfuchs, Marianna Tampere
     host_organisation: Karolinska Institute
     use: "The network promotes collaboration between BSL3 facilities by sharing experience, knowledge and technology. The network has identified focus points and specific capabilities of each BSL3 facility to ensure maximal use of existing capabilities."
     access: "The network is open to Swedish BSL3 facilities in academia and government. BSL3 users, support staff and management are welcome to join. To join the network, please send an email to [[email protected]](mailto:[email protected])."
     data_etc: "N/A"
     publications_etc:
     webpage: "[ki.se/en/research/swedish-bsl3-network](https://ki.se/en/research/swedish-bsl3-network)"
-    contact: "Marjo-Riitta Puumalainen<br>Coordinator Swedish BSL3 Network<br>Email: [marjo-riitta.puumalainen@ki.se](mailto:marjo-riitta.puumalainen@ki.se)<br><br>Antonio Gigliotti Rothfuchs<br>BSL3 Director<br>Email: [[email protected]](mailto:[email protected])"
+    contact: "Marianna Tampere<br>Coordinator Swedish BSL3 Network<br>Email: [marianna.tampere@ki.se](mailto:marianna.tampere@ki.se)<br><br>Antonio Gigliotti Rothfuchs<br>BSL3 Director<br>Email: [[email protected]](mailto:[email protected])"
 ---
 
 High-level containment laboratories are a cornerstone for pandemic laboratory preparedness. The purpose of the Swedish BSL3 Network is to strengthen national pandemic laboratory preparedness by improving interactions between BSL3 facilities in the country.

content/english/resources/bsl3.md

@@ -5,7 +5,7 @@ resource_info:
     name: "BSL3 Biomedicum-SciLifeLab Collaborative Platform"
     pi: Antonio Rothfuchs
     host_organisation: Karolinska Institute
-    contact: "Marjo-Riitta Puumalainen<br>Coordinator Swedish BSL3 Network<br>Email: [marjo-riitta.puumalainen@ki.se](mailto:marjo-riitta.puumalainen@ki.se)<br><br>Antonio Gigliotti Rothfuchs<br>BSL3 Director<br>Email: [[email protected]](mailto:[email protected])"
+    contact: "Marianna Tampere<br>Coordinator Swedish BSL3 Network<br>Email: [marianna.tampere@ki.se](mailto:marianna.tampere@ki.se)<br><br>Antonio Gigliotti Rothfuchs<br>BSL3 Director<br>Email: [[email protected]](mailto:[email protected])"
 for_background_table:
     pi: Antonio Rothfuchs
     pi_affiliation: Karolinska Institute

content/svenska/dashboards/post_covid.md

@@ -86,6 +86,10 @@ Geografisk fördelning av diagnostiserade fall i förhållande till befolkningss
 
 **Källkod som används för att skapa visualisering:** [Källkod som används för databeredning](https://github.com/ScilifelabDataCentre/covid-portal-visualisations/blob/main/postCOVID/postcovid_dataprep.py), [Källkod som används för att skapa kartan](https://github.com/ScilifelabDataCentre/covid-portal-visualisations/blob/main/postCOVID/postcovid_mapfig_population_U089.py).
 
+<!--
+
+{{/* The data used for this is not available anymore, this section should be removed if no alternatives found */}}
+
 ### Geografisk fördelning av diagnostiserade fall relativt antal bekräftade fall
 
 Kartorna nedan visar antal individer som fått diagnoskoderna av intresse per län angivet i procent av det totalt antal bekräftade fall av covid-19 i länet (baserat på [data från Folkhälsomyndigheten](https://www.folkhalsomyndigheten.se/smittskydd-beredskap/utbrott/aktuella-utbrott/covid-19/statistik-och-analyser/bekraftade-fall-i-sverige/)). Antal bekräftade fall bygger på kumulativa antalet positiva covid-19-test i regionen vid det datum som anges för den senaste uppdateringen av diagnoskoderna av intresse. Både totalt antal bekräftade fall av covid-19 och antal personer med diagnoskod av intresse kan ses genom att scrolla över ett visst län. Observera att de data som visualiseras på kartan bör tolkas med försiktighet. Antal bekräftade fall av covid-19-fall är sannolikt en underskattning. Individer som har covid-19 kan vara asymptomatiska och alla individer med covid-19 symtom testas inte och ingår inte i de rapporterade bekräftade fallen. Diagnoserna relaterade till postcovid introducerades vid olika tillfällen, och alla patienter kanske inte ännu fått en formell diagnos.
@@ -106,6 +110,8 @@ Kartorna nedan visar antal individer som fått diagnoskoderna av intresse per l
 
 **Källkod som används för att skapa visualisering:** [Källkod som används för databeredning](https://github.com/ScilifelabDataCentre/covid-portal-visualisations/blob/main/postCOVID/postcovid_dataprep.py), [Källkod som används för att skapa kartan](https://github.com/ScilifelabDataCentre/covid-portal-visualisations/blob/main/postCOVID/postcovid_mapfig_cases_U089.py).
 
+-->
+
 ### Vanligaste diagnosgrupper som rapporterats tillsammans med U09.9 Postinfektiöst tillstånd efter covid-19 (postcovid)
 
 #### Diagnoskod U09.9