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- Klionsky, Daniel J., et al.
(author)
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Guidelines for the use and interpretation of assays for monitoring autophagy
- 2012
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In: Autophagy. - : Informa UK Limited. - 1554-8635 .- 1554-8627. ; 8:4, s. 445-544
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Research review (peer-reviewed)abstract
- In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.
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- Botvinik-Nezer, Rotem, et al.
(author)
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Variability in the analysis of a single neuroimaging dataset by many teams
- 2020
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 582, s. 84-88
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Journal article (peer-reviewed)abstract
- Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses(1). The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset(2-5). Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed. The results obtained by seventy different teams analysing the same functional magnetic resonance imaging dataset show substantial variation, highlighting the influence of analytical choices and the importance of sharing workflows publicly and performing multiple analyses.
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- Li, Ronggui, et al.
(author)
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Deletion of exon I of SMAD7 in mice results in altered B cell responses
- 2006
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In: Journal of Immunology. - 0022-1767 .- 1550-6606. ; 176:11, s. 6777-6784
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Journal article (peer-reviewed)abstract
- The members of the TGF-beta superfamily, i.e., TGF-beta isoforms, activins, and bone morphogenetic proteins, regulate growth, differentiation, and apoptosis, both during embryonic development and during postnatal life. Smad7 is induced by the TGF-beta superfamily members and negatively modulates their signaling, thus acting in a negative, autocrine feedback manner. In addition, Smad7 is induced by other stimuli. Thus, it can fine-tune and integrate TGF-beta signaling with other signaling pathways. To investigate the functional role(s) of Smad7 in vivo, we generated mice deficient in exon I of Smad7, leading to a partial loss of Smad7 function. Mutant animals are viable, but significantly smaller on the outbred CD-1 mouse strain background. Mutant B cells showed an overactive TGF-beta signaling measured as increase of phosphorylated Smad2-positive B cells compared with B cells from wild-type mice. In agreement with this expected increase in TGF-beta signaling, several changes in B cell responses were observed. Mutant B cells exhibited increased Ig class switch recombination to IgA, significantly enhanced spontaneous apoptosis in B cells, and a markedly reduced proliferative response to LPS stimulation. Interestingly, LPS treatment reverted the apoptotic phenotype in the mutant cells. Taken together, the observed phenotype highlights a prominent role for Smad7 in development and in regulating the immune system's response to TGF-beta.
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- Negre, Nicolas, et al.
(author)
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A cis-regulatory map of the Drosophila genome
- 2011
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 471:7339, s. 527-531
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Journal article (peer-reviewed)abstract
- Systematic annotation of gene regulatory elements is a major challenge in genome science. Direct mapping of chromatin modification marks and transcriptional factor binding sites genome-wide(1,2) has successfully identified specific subtypes of regulatory elements(3). In Drosophila several pioneering studies have provided genome-wide identification of Polycomb response elements(4), chromatin states(5), transcription factor binding sites(6-9), RNA polymerase II regulation(8) and insulator elements(10); however, comprehensive annotation of the regulatory genome remains a significant challenge. Here we describe results from the modENCODE cis-regulatory annotation project. We produced a map of the Drosophila melanogaster regulatory genome on the basis of more than 300 chromatin immunoprecipitation data sets for eight chromatin features, five histone deacetylases and thirty-eight site-specific transcription factors at different stages of development. Using these data we inferred more than 20,000 candidate regulatory elements and validated a subset of predictions for promoters, enhancers and insulators in vivo. We identified also nearly 2,000 genomic regions of dense transcription factor binding associated with chromatin activity and accessibility. We discovered hundreds of new transcription factor co-binding relationships and defined a transcription factor network with over 800 potential regulatory relationships.
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