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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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| 2. |
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| 3. |
- Beal, Jacob, et al.
(author)
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Robust estimation of bacterial cell count from optical density
- 2020
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In: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 3:1
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Journal article (peer-reviewed)abstract
- Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data.
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| 5. |
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- 2019
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Journal article (peer-reviewed)
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| 6. |
- Li, Jian Feng, et al.
(author)
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Transcriptional landscape of B cell precursor acute lymphoblastic leukemia based on an international study of 1,223 cases
- 2018
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In: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424. ; 115:50, s. 11711-11720
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Journal article (peer-reviewed)abstract
- Most B cell precursor acute lymphoblastic leukemia (BCP ALL) can be classified into known major genetic subtypes, while a substantial proportion of BCP ALL remains poorly characterized in relation to its underlying genomic abnormalities. We therefore initiated a large-scale international study to reanalyze and delineate the transcriptome landscape of 1,223 BCP ALL cases using RNA sequencing. Fourteen BCP ALL gene expression subgroups (G1 to G14) were identified. Apart from extending eight previously described subgroups (G1 to G8 associated with MEF2D fusions, TCF3–PBX1 fusions, ETV6–RUNX1–positive/ETV6–RUNX1–like, DUX4 fusions, ZNF384 fusions, BCR–ABL1/Ph–like, high hyperdiploidy, and KMT2A fusions), we defined six additional gene expression subgroups: G9 was associated with both PAX5 and CRLF2 fusions; G10 and G11 with mutations in PAX5 (p.P80R) and IKZF1 (p.N159Y), respectively; G12 with IGH–CEBPE fusion and mutations in ZEB2 (p.H1038R); and G13 and G14 with TCF3/4–HLF and NUTM1 fusions, respectively. In pediatric BCP ALL, subgroups G2 to G5 and G7 (51 to 65/67 chromosomes) were associated with low-risk, G7 (with ≤50 chromosomes) and G9 were intermediate-risk, whereas G1, G6, and G8 were defined as high-risk subgroups. In adult BCP ALL, G1, G2, G6, and G8 were associated with high risk, while G4, G5, and G7 had relatively favorable outcomes. This large-scale transcriptome sequence analysis of BCP ALL revealed distinct molecular subgroups that reflect discrete pathways of BCP ALL, informing disease classification and prognostic stratification. The combined results strongly advocate that RNA sequencing be introduced into the clinical diagnostic workup of BCP ALL. four decades, most of the recurring chromosomal abnormalities, including aneuploidy, chromosomal rearrangements/gene fusions (e.g., ETV6–RUNX1, BCR–ABL1, and TCF3–PBX1), and rearrangements of KMT2A (previously MLL), were identified by.
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