Homology-directed repair of a defective glabrous gene in Arabidopsis with Cas9-based gene targeting [Florian Hahn, Marion Eisenhut, Otho Mantegazza, Andreas P.M. Weber, January 5, 2018, BioRxiv] [https://doi.org/10.1101/243675]Overview and take-home messages: Hahn et al. have compared the efficiencies of two different methods that have been previously reported to enhance the frequency of homologous recombination in plants. The paper has focused on testing a viral replicon system with two different enzymes, nuclease and nickase, as well as an in planta gene targeting (IPGT) system in Arabidopsis thaliana. Interestingly, authors have chosen GLABROUS1 (GL1), a regulator of trichome formation, as a visual marker to detect Cas9 activity and therefore homologous recombination. A 10 bp deletion in the coding region of GL1 gene produces plants devoid of trichomes. Out of the two methods in planta gene targeting approach successfully restored trichome formation in less than 0.2% of ~2,500 plants screened, whereas the method based on viral replicon machinery did not manage to restore trichome formation at all. This manuscript is of high quality, experiments are well designed and executed. However, there are some concerns that could be addressed in the next preprint or print version. Below are some feedback and suggestions that we hope will improve the manuscript.
This is a preprint journal club review of "Exotic species dominate due to niche overlap in a complex grassland community" by Lawrence H. Uricchio, S. Caroline Daws, Erin R. Spear and Erin A. Mordecai. Te preprint was originally posted on bioRxiv on January 15, 2018 (DOI: https://doi.org/10.1101/253518) https://www.biorxiv.org/content/early/2018/01/24/253518. Our group Biotic Interactions and Global Change (BIGC) reviewed this paper in February 2018.
I started writing this memo while on an airplane, flying back from sunny San Diego. While definitely one of the highlights of the trip, the sunshine was not the reason for my visit to Southern California. Instead, I was there with hundreds of other auditory neuroscientists from all over the world to attend the 41th MidWinter Meeting of the Association for Research in Otolaryngology (ARO).
This is a review of the preprint "Frequent lack of repressive capacity of promoter DNA methylation identified through genome-wide epigenomic manipulation" by Ethan Edward Ford, Matthew R. Grimmer, Sabine Stolzenburg, Ozren Bogdanovic, Alex de Mendoza, Peggy J. Farnham, Pilar Blancafort, and Ryan Lister.The preprint was originally posted on bioRxiv on September 20, 2017 (DOI: https://doi.org/10.1101/170506).
Medicago truncatula Zinc-Iron Permease6 provides zinc to rhizobia-infected nodule cells [Isidro Abreu, Angela Saez, Rosario Castro-Rodriguez, Viviana Escudero, Benjamin Rodriguez-Haas, Marta Senovilla, Camille Laure, Daniel Grolimund, Manuel Tejada-Jimenez, Juan Imperial, Manuel Gonzalez-Guerrero , January 24, 2017 (preprint), September 21, 2017 (in print), BioRxiv & Wiley-Blackwell]
This report was prepared by Vienna Biocenter Summer Class 2017 PhD students as a part of their Priming Your PhD training. Please see the instructors and participating students’ names at the end of the review. Shoemaker et al. performed a systematic genome wide CRISPR screen and identified a catalogue of factors involved in mammalian autophagy. They validated their findings by further characterizing one of the newly identified autophagy-related factors in their screen. They showed that TMEM41B, an integral ER-membrane protein is involved in maturation of the phagophore. Furthermore, using NBR1 as an autophagy substrate, they discovered a number of genes involved in a novel non-canonical autophagy pathway, which is independent of ATG7. The comprehensive results obtained in this study make the picture of mammalian autophagy more complete, and provide entry points for future studies that will dissect alternative autophagy pathways and the molecular mechanism underlying the role of TMEM41B in canonical autophagy. Genome wide CRISPR-screen provides a state of the art, unbiased approach to discover unknown genes in the autophagy process. They have developed a sensitive autophagic flux measurement reporter using the tandem-fluorescent reporters. In addition to the commonly used LC3B, they have also used known cargo receptors to identify autophagy regulators. Using this reporter system as a readout for a genome-wide screen is opening up the possibility to systematically dissect complex cellular autophagy networks. The authors were able to validate their screening approach by recovering almost all known ATG factors. Interestingly, the screen also identified a number of completely new candidates. While the authors have initially setup screens to address the pathways involved in the five major autophagy receptors, their last screening setup also allows to dissect the pathway involved in the highly debated ATG7-independent lysosomal targeting. We find this particularly interesting as is significantly contributes to our general understanding of how the network of autophagy receptors is organized. Furthermore, the description of ATG-independent alternative autophagy pathways questions the use of ATG7 KO genotypes as a control in autophagy experiments. As autophagy may still be active in ATG7 KO, this should be of concern for future experimental designs. The authors extensively stress-tested their reporter systems prior to performing the screen. They have also integrated all the reporters in the same loci to prevent expression level differences. The authors, in most cases, transparently provide numbers of cells used in the experimental setup and respective controls. Throughout the paper the authors confirm and cross-reference results obtained from other researchers in the field. They have used a broad range of experimental tools to validate their screen and results. Overall, the manuscript is of very high quality. Below are some suggestions that we hope will improve the manuscript. 1. The authors have chosen a 60% interval for their FACS sorting range. It would be useful if they provide the original FACS plots (RFP/GFP ratio), in order for us to see how the distribution of non-infected and library-infected populations look like. This would explain why screening for 60% of the population is necessary/reasonable. Although they have used a published sgRNA library, it would have been useful if they provided more information such as how many sgRNAs/gene are in the initial library, library representation in the transduced cell pool, replicate correlation plots. In addition, previous CRISPR screen papers have used fold changes for quantifying their hits. It would be useful if the authors explain the rationale behind beta scores and give more detail on beta score calculation. 2. There is also no information about Cas9 clonality in the K562 cells which were used for the screen. This would be useful for readers. 3. In the validation experiments, the authors state “mock treated cells” as negative control – does this mean that no sgRNA is transduced? If so, this is not an applicable negative control, as biological response to transduction and DNA damage repair by introducing an sgRNA is not addressed. Therefore, using a sgRNA targeting a gene desert would be the correct control. 4. Information how they normalized to 1.0 in Fig 3A is missing, as well as additional labels on Y-Axis that would enable the reader to understand whether this is a linear or log-scale. 5. In Figure 6, Stx17 and one of the cargo receptors could have been nice controls. Additionally, it would have been nice to have EM images of autophagosomes in TMEM41B KO cells. 6. Due to the design of the screen, one would have expected to get some hits related to lysosomal acidification. The authors did not mention this in the results or discussion. It would be nice to at least discuss this. Similarly, the authors should compare and contrast DeJesus et al., 2017 eLife paper in the discussion. This paper uses a similar CRISPR approach and looks for autophagy regulators. 7. In the introduction, it would have been beneficial to introduce the SQSTM1 receptors in a bit more detail, since the screen is based on them. 8. It would be useful if they clarified why they decided to use TMEM41B, since it wasn’t a very strong hit for all the receptors tested. 9. The description of the cell line used for the screen was unclear; were single clones or a bulk population used? 10. Figure S6 is missing; the supplementary figures go from Figure S5 to S7. 11. In the text, RAB7A and HOPS are mentioned while referring to figure 7E. However, these factors cannot be found in the figure. 12. The last paragraph of the results section refers to an analysis about genetic interactions between ATG7 and several factors, but no figure is ever referenced for this section. 13. Figure 3A: in the legend, more information could be given as to what exactly is plotted and less regarding the supplementary data. It is difficult to determine the scale of the Y-axis as only two values are given. PhD Students: Krista Briedis, Alexander Bykov, Claudia Ctortecka, Melanie De Almeida, Philipp Dexheimer, Joachim Garbrecht, Sarah Gruenbacher, Bence Hajdusits, Felix Holstein, Bhagyshree Jamge, Friederike Leesch, Joanna Nowacka, Mina Petrovic, Anna Schmuecker, Monika Steininger, Pietro Tardivo, Szu-Hsien Wu Facilitators: Fumiyo Ikeda, Yasin Dagdas
Here is how it all started. Two researchers and ASAPbio Ambassadors met at a Mozilla Working Open Workshop in April 2017. A PhD student (Daniela) and a postdoctoral fellow (Sam) decided to volunteer some of their time to develop guidelines to help researchers from all around the world start preprint journal clubs. We believed this would have contributed positively to spreading the word and value of preprints in the scientific community, as well as helped early-career researchers master their skills in peer review.During the Mozilla Science Global Sprint, June 2-3 2017, we wrote our application to the first Mozilla Science Mini-Grant. We asked for enough money to support 20 beta testers by covering the cost of snacks and beverage for two preprint journal clubs. And we were awarded!Since then, a lot has happened, including starting PREreview thank to the help of the Authorea team and the support of many others who share our mission.Since July, our application has been posted on our project GitHub, but we wanted to have it on PREreview as well. So below is our full proposal. Thank you!
This is a preprint journal club review of "Evolutionary responses to conditionality in species interactions across environmental gradients" by Anna M O'Brien, Ruairidh J.H. Sawers, Jeffrey Ross-Ibarra, Sharon Y Strauss. The preprint was originally posted on bioRxiv on December 10, 2017 (DOI: https://doi.org/10.1101/031195) https://www.biorxiv.org/content/early/2017/12/10/031195.Our group Biotic Interactions and Global Change (BIGC) reviewed this paper on January, 2017 .
This is a preprint journal club review of K-Means Method for Clustering Water Quality Status on The Rivers of Banjarmasin by Tien Zubaidah and Nieke Karnaningroem. The preprint was originally posted on INArxiv on December 21, 2017 (link: https://osf.io/g6wkp/). The article is now in review in the ARPN Journal of Engineering and Applied Sciences (submitted December 20, 2017). Original abstract: The surface river water quality in Banjarmasin city tends to decline constantly as the result of direct and indirect waste disposal from various human activities along the river body. This study aimed to determine the vulnerability points against pollution in the rivers of Banjarmasin using clustering techniques with K-means algorithm. The parameters observed include Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Suspend Solid (TSS) and Dissolved Oxygen (DO). The data were collected at eight water monitoring stations on various rivers in Banjarmasin city. With the K-means method, four water quality status were clustered. The result showed that 6 stations observed during the period April to October 2016 were categorized into the heavy polluted cluster with major pollution point of sources came from the domestic and industrial activities.
In our journal club this week, we went a little more experimental and selected a BioRxiv paper yet to be published - it can be found at https://www.biorxiv.org/content/early/2017/07/13/163402 and currently bears the title "Heterogeneous Responses of Hematopoietic Stem Cells to Inflammatory Stimuli are Altered with Age". We were inspired by the eLife Labs article on PREReview to give this a go and hopefully the authors and wider biological community benefit from this interaction.As mentioned above, this was our first attempt at discussing a preprint paper from BioRxiv so we had a few opening questions and general discussion about the concept between the 15 or so members of the journal club. Our groups (Laurenti and Kent) are based at the WT / MRC Cambridge Stem Cell Institute in Cambridge, UK (https://www.stemcells.cam.ac.uk/) and the opinions and comments found below are a summary of the group discussion rather than the opinion of any single researcher partaking in the journal club.First question: Was reading this any different than a normal paper?Some people had worried that a pre-publication paper would suffer from major gaps in organisation or presentation and this was not the case here. Overall, there was not a substantial difference from published papers and people agreed that the structure of the paper was good and the content relatively easy to follow. That said, one cynical comment was raised, querying whether the peer review process prohibited authors from telling their version of the story (e.g., one interpretation), that might actually diverge from the interpretation of the broader field (i.e., peer review makes the article "less readable" but also "more accurate"). Second question: Would you continue to explore pre-print servers for new content?Resounding "yes" from majority of researchers (many of whom had not heard of preprint servers prior to the discussion)---We then entered the discussion phase and came up with the following "review" based on the discussion:In their manuscript, "Heterogeneous Responses of Hematopoietic Stem Cells to Inflammatory Stimuli are Altered with Age", Mann et al., identify and transcriptionally profile at the single cell level a novel subset of aged cells primed to respond to inflammatory stimuli. Overall, the manuscript read very well, had a logical progression and was easily considered to be "publication standard" with respect to these aspects (i.e., it was in better shape from an editing perspective than some manuscripts!). The data were presented nicely and generally supported the statements in the abstract, but several areas of concern were identified through our discussion and a number of questions arose that might be considered by the authors: Concerns:1) Unknown LT-HSC frequency of cells isolated from aged animals: LSK SLAM is a well-described phenotype for functional HSCs in young mice (~35-50% functional HSCs), but it remains unknown what the precise frequency of functional HSCs in that phenotype in aged mice would be. Perhaps the best evidence comes from the de Haan group (http://jem.rupress.org/content/208/13/2691.long) where they studied LSK SLAM 34- EPCR+ cells and showed that there was at least 2-fold less functional activity on a per HSC basis and this arguably is a much more stringent sorting criteria. Therefore, the cells being isolated as "aged LT-HSCs" in this current manuscript are likely less than 10% functional HSCs, making interpretation of all downstream data difficult to ascribe to "LT-HSCs". Moreover, the frequency of phenotypic LT-HSCs is highly variable (from 100 to 4300 per million cells), making the number of input mice (n=4) concerning, since they might represent a large proportion of one single mouse (e.g., 100-fold more phenotypic HSCs). Overall, our discussion group agreed that the data presented re: inflammatory signatures were still interesting - it was just that the claims that it was a functional LT-HSC specific (or myeloid-biased LT-HSC specific) signature were less robust.2) Proportional, not absolute, changes in chimerism: Figure 1 appears to display the proportion of cells that were T, B, gran, or myeloid without showing the absolute levels of chimerism. It therefore precludes any reviewer from appropriately determining whether a "myeloid bias"really exists (e.g., an absolute increase in myeloid cell production) or whether it is an absence of lymphoid cell production (lymphoid deficient). Without differences in the absolute myeloid cell number, it changes the interpretation of the data since both cell types would produce the same number of cells and young myeloid progenitors would be present (but not responding) to the stimulus.3) in vitro 2h stimulus vs. in vivo effect: The in vivo effect of a single dose treatment seems to be temporary (Figure 1 B-E), whereas the in vitro effect (from a 2 hr stimulation) is sufficient to change the fate of the aged LT-HSCs that get transplanted. It remains unclear how the progeny of these LT-HSCs continue to self-renew in a way which creates progeny HSC with the same properties for sustaining long term hematopoiesis. A few items came up in discussion: 1) Is there selective killing of balanced/lymphoid biased HSCs? 2)Are secondary transplantations "myeloid-biased" as well (e.g., how strong is the continuation of the pattern?)Additional questions arising in discussion:1) Could the authors speculate on the origin of the HSC expansion? It has been described by several groups that the HSC subtype balance shifts with age but nobody has clearly addressed whether the lymphoid deficient HSCs that accumulate with age are "old" balanced HSCs that have lost lymphoid potential or an accumulation of "lymphoid deficient (or alpha / My-biased)" HSCs. 2) Would young HSCs from malignant mouse models (or patient samples) also bear the aged/inflammatory signature?minor items:the mega-biased HSCs were first described by the Jacobsen and Nakauchi groups, not the de Haan and Graf groups as mentioned in discussion.
Hello! Thank you to all who came to our preprint workshop at UCL 30th October, 2017. We thoroughly enjoyed the discussion and we hope it was useful to you too. Due to the superb note-taking skills of Naomi Penfold, I am able to provide a detailed summary of the event as a refresher for those who came, and as info for those who couldn't make it. If you are interested in hosting your own preprint event and would like some help, please let me know (firstname.lastname@example.org). Enjoy!
Metabolic Interactions Between Dynamic Bacterial Subpopulations Adam Z Rosenthal, Yutao Qi, Sahand Hormoz, Jin Park, Sophia Hsin-Jung Li, Michael ElowitzVersion reviewed: V1. October 25, 2017. bioRxiv 208686; doi: https://doi.org/10.1101/208686Note: This review incorporates input from attendees to the ITQB Preprint Journal Club on November 9, 2017.Overview:Rosenthal et al. demonstrate that stochastic changes between metabolic gene expression states underlie the population-averaged progression through acetate production to acetoin detoxification during exponential growth of B. subtilis. They show that the probabilities of cells being in the slow-growing, acetate-producing (sucC+) and acetoin-producing (alsS+) states depend upon competence regulators (comK) as well as environmental acetate concentration. The work combines population averaged experiments with single-cell fluorescence snapshot and timelapse microscopy experiments to conclusively prove the claims in the abstract. The work was very interesting for members of our journal club coming from several different fields. We were particularly interested in the the implications of the final gel-pad timelapse experiment and its discussion in the main text—the possibility that competence, toxic-product secretion, and subsequent detoxification could be coupled to give B. subtilis an advantage in a complex environment will be a great problem to investigate in the future.