dataesr/scientific-paragraphs-categorization huggingface dataset:
NOX2 Complex Subunits Are Depleted in LSCs and at Relapse In order to verify whether NOX can contribute to AML aggressiveness, we investigated the expression of NOX-coding genes in LSCs and in relapsed AML cells. First, we explored the NOX-expression profile in functionally-defined LSCs using a dataset (GSE76009) of mouse-engrafting primary human AML stem cells (LSC + ) and non-engrafting LSCdepleted (LSC -) cells  [33]. The expression of the catalytical subunits was examined according to the expression status of the CD34 and CD38 cell surface markers. CYBB was the most expressed gene, compared to NOX1, NOX3-5 and DUOX1/2 (Figure  S1a ). The expression of CYBB was weak in CD34 + CD38 -cells, which are enriched in LSC activity, but increased with the loss of the CD34 marker in more committed cells.
The expression of NOX2 complex regulatory subunits, save for NCF4, was strongly induced in more differentiated CD34 -CD38 + cells (Figure  S1b ). In line with this, NOX2 complex genes, except NCF4, were downregulated in LSC + compared to LSC -cells (Figure  4a ), indicating that cells with LSC properties have a lower expression of genes coding for the components of the NOX2 complex compared to more committed cells. Next, we examined the expression of NOX2 complex genes in AML samples from the GSE66525 dataset at relapse and diagnosis  [32]. Consistent with the observation in LSCs, we found a global decrease in the expression of NOX2 genes at relapse compared to diagnosis, except for NCF4 (Figure  4b ). Interestingly, an LSC signature has been reported in AML blasts at relapse for this dataset  [32].
NOX Activity Is Only Detectable after PMA-Induction, Mainly in M4 and M5 AML Subtypes The in silico meta-analysis of the primary AML datasets showed that NOX2 expression is associated with the differentiation stage of AML cells, suggesting that this complex may contribute to ROS production, at least in the M4 and M5 subtypes, with a possible contribution to blast proliferation and differentiation blockage. Previous studies have shown NOX expression and suggested that NOX activity contributes to AML cell proliferation and differentiation  [6, 26, 27]. However, these studies mostly measured ROS production and NOX activity after stimulation or under stress conditions, which can reveal the potential rather than the contribution of NOX to global ROS production in a steady-state. In order to verify whether NOX actively contributes to ROS production in AML cells, we examined NOX mRNA levels, together with NOX activity in the absence of stress.
In line with this, NOX2 complex genes, except NCF4, were downregulated in LSC + compared to LSC -cells (Figure  4a ), indicating that cells with LSC properties have a lower expression of genes coding for the components of the NOX2 complex compared to more committed cells. Next, we examined the expression of NOX2 complex genes in AML samples from the GSE66525 dataset at relapse and diagnosis  [32]. Consistent with the observation in LSCs, we found a global decrease in the expression of NOX2 genes at relapse compared to diagnosis, except for NCF4 (Figure  4b ). Interestingly, an LSC signature has been reported in AML blasts at relapse for this dataset  [32]. In order to address the negative correlation with chemoresistance, we examined the expression profile of genes coding for the NOX2 complex in nine cell lines that are adapted to resist 1 µM of cytarabine (Ara-C) in vitro.
Discussion Reactive oxygen species play a major role in AML progression. While quiescent LSCs have low levels of ROS, a higher level drives the proliferation of the more mature and metabolically-active blasts. Previous studies have postulated that NOX are central in LSCs, blast proliferation, and differentiation blockage in AML; however, their contribution to ROS production in AML has not been fully addressed. In this study, we provided a thorough profiling of NOX expression and activity in AML cells using a meta-analysis of public expression datasets, including 839 AML samples of various cytogenetic and molecular subtypes, and the in vitro examination of 24 myeloid leukemia cell lines. Our results demonstrate that genes coding for the NOX2 complex are ubiquitously expressed across blast samples and AML cell lines, and are the most expressed among the 13 NOX genes, in agreement with recent findings  [27].
It is worthy of note that although NOX4 expression has been previously described downstream of FLT3-ITD in AML cells  [28, 54, 55] , our transcriptional analyses, using three different technologies (microarrays, RNA-seq and qRT-PCR), established that its mRNA expression is lacking from all AML subtypes, including FLT3-ITD. This indicates a possible transcriptional regulation of NOX4 mRNA or high protein stability. The in-depth survival analysis of the primary AML datasets did not reveal significant prognostic values for CYBB, NCF1, and NCF2 genes, despite a high correlation with three cytogenetic subgroups. In fact, while the t(8;21) and inv  (16)  subgroups are both associated with good prognosis, they showed opposite expression profiles of NOX2 genes, which could partly explain the lack of consistent global prognosis for NOX.
We also noticed high heterogeneity in the NOX profiles within most cytogenetic subgroups, suggesting distinct cellular properties between patients. Our data further show that NOX2 complex subunits are increased in AML cells from the M4 and M5 FAB stages, both at the RNA and protein levels. This is in line with previous observations at the protein level  [26, 56]. We also found a significant correlation between the mRNA and protein levels for NOX2-regulatory subunits in our cell lines, indicating that the transcriptomic analysis could be reflective of NOX proteins in AML blasts. Interestingly, three NOX2 subunits (CYBB, NCF2 and NCF4) are among a set of 311 genes which we recently identified as being consistently downregulated in the bone marrow (BM) of AML patients from various cytogenetic subgroups, compared to healthy controls  [57].
Besides this, a correlation between NOX expression and differentiation was established in normal hematopoiesis, in which an increased Nox2 expression and ROS production have been observed in murine granulocyte-monocyte progenitors. However, when we examined 24 AML cell lines, we found that they all lacked detectable NOX activity in the absence of exogenous stimulation. This suggests that NOX2 requires further assembly for its activation in AML cells. In agreement with this, Reddy et al. reported no involvement of NOX in ROS production and oxygen consumption in AML cell lines harboring different tyrosine kinase mutations  [25]. Together, these data challenge the previous findings showing a contribution of NOX to ROS production in AML  [6]. In fact, Hole et al. reported an endogenous NOX activity in primary AML samples independently of FAB subtypes  [6] ; however, this study relied on unsorted mononuclear cells, which could be biased by the presence of phagocytes that are characterized by high NOX2 activity.
In line with our findings, Hole et al. used PMA stimulation to measure the NOX2 activity in THP-1 cells  [6] , confirming the lack of endogenous activity in AML cell lines without stimulation. Our data further suggest that increased ROS levels in AML blasts are unlikely to be driven by NOX activity. However, NOX2-generated ROS was recently reported as a key signal for the induction of mitochondrial transfer from stromal cells to AML blasts, as well as in the reduced oxygen consumption  [27] ; however, these studies did not directly measure the NOX activity in AML cells. Consequently, whether the AML cells in their microenvironment possess an endogenous NOX activity remains an open question. In our study, the KD of CYBB in AML cell lines did not affect the cell proliferation or their differentiation potential.
Moreover, the functional data reported in this study highlight the effect of CYBB KD on AML cell lines under steadystate conditions in vitro. Hence, additional studies are needed to investigate the role of the NOX2 complex under stress conditions, and in the context of primary AML blasts in their microenvironment, or even in animal models in vivo. Furthermore, and importantly, the weak expression of genes coding for the NOX2 complex in LSCs does not necessarily rule out the possibility of weak NOX activity in these cells. Therefore, the investigation of the role of CYBB KD in human LSCs is also worth considering in future studies.
Conclusions In summary, this work shows that NOX2 is the only NOX complex expressed in AML cells with higher expression in AML committed in the myelomonocytic and monocytic differentiation stages, in contrast to the low expression in LSC and relapsed AML. NOX expression, although it is deregulated in favorable cytogenetic groups, did not correlate with AML prognosis. No endogenous NOX activity was observed in AML cell lines in vitro, although many are inducible upon stimulation. Besides this, CYBB KD did not affect the proliferation and differentiation of AML cell lines in vitro. Altogether, our data suggest that NOX genes are differentiation markers with no intrinsic role in AML cells.
Supplementary Materials: The following are available online at https://www. mdpi. com/2076-3 921/10/3/498/s1, Figure  S1 : Expression profile of genes coding for NOX2 subunits according to CD34/CD38 status in AML primary cells from the GSE76009 dataset. Figure  S2 : Transcriptional profile of genes coding for NOX2 subunits following their adaptation to cytarabine (Ara-c) in vitro. Figure  S3 : protein expression profiles of NOX2 regulatory subunits in AML cell lines and their correlation with RNA levels. Figure  S4 : THP1 proliferation, as measured by the resazurin assay. Table  S1 : List of the used cell lines and their culture media. Table  S2 : Primer sequences for qRT-PCR. Table  S3 : Summary of the NOX expression in three AML datasets. Table  S4 : NOX expression according to cytogenetic abnormalities in the three AML expression datasets.
Antioxidants 2021 , 19 Figure 1. 2021191 Figure 1. Expression profile of genes coding for CYBB, NCF1, and NCF2 in primary AML, according to cytogenetic abnormalities. (a) Schematic representation of the seven NOX complexes (NOX1-5 and DUOX1-2) and their 13 subunits. The analysis was performed in the (b) GSE6891, (c) GSE10358, (d) TCGA datasets. Student's t-test followed by Benjamini-Hochberg (BH)-adjustment was used to compare each karyotype to all of the others combined. **: p < 0. 01; ***: p < 0. 001. CN: cytogenetically normal. IRC: intermediate risk cytogenetics. PRC: poor risk cytogenetics.
Study design and participants In this cross-sectional study carried out from December 2017 to July 2019, data were collected from children under 6 consulting at hospitals including Centre-Hospitalier-Universitaire Mère-enfant, de la Lagune, Centre-Hospitalier-Universitaire of Suruléré, and Ménontinin Hospital, in Cotonou, Benin, l'Oueme/Plateau Hospital in Porto-Novo, and Ouidah Hospital in Ouidah. Porto-Novo is 41. 2 km east of Cotonou, while Ouidah is 39 Km west of Cotonou, both settings share the same climate as Cotonou. Children were recruited in the study if they presented a positive rapid diagnostic test for P. falciparum (DiaQuick-Malaria-P. falciparum-Cassette, Dialab; Hondastrasse, Austria) and meet the World Health Organization clinical malaria de nition criteria (WHO; 2011). All malaria cases were de ned as a microscopically con rmed P.
Statistical analysis All statistical analysis was conducted with Stata software v15 and GraphPad Prism v9. Continuous variables and categorical variables were compared between the three clinical groups (CM, SM, and UM) using the Kruskal-Wallis test in conjunction with Dunn's multiple comparison post-hoc tests and chisquare test respectively. The levels of analytes were compared between the groups, UM vs SM/CM, survived vs died and deep coma vs no deep coma among severe cases using Mann-Whitney U-test and binary logistic regression. Linear regression was used to examine the relationship between analyte levels and platelets, hemoglobin, leucocytes, glycemia, parasitemia, and age. Signi cance levels was set at P-value <0. 05. The validity of each molecule as biomarker for malaria related severity, coma and fatality was assessed by Receiver Operating Characteristic (ROC) curve analysis, a two-dimensional measure of classi cation performance where the area under the ROC curve (AUROCC) accurately measures discrimination, i.
Funding: This work was supported by the  Merieux Institut Research Grant  (MRG) from  Institut Mérieux at Lyon France ; The  Institut de Recherche pour le Développement (IRD)  at  Marseille France , the  SCAC -Cultural  and  Cooperation Department -French Embassy in Ghana , and The  Danish International Development Agency (DANIDA). Figure 4 Assessment by ROC curve analyses of the individual prediction performance of sTie-2, PCT, Ang-2, PTX3, suPAR, sEPCR to differentiate for severe cases on the day of admission to hospital. The area under the curve as well as the con dence intervals are indicated in the legend. * indicates 0. 01<p value  <0. 05 , **0. 001< p value<0. 01, *** indicates p value  ≤0. 001.
The Illumina paired-end sequencing (2 Â 150-bp format) was performed as described (4). For MinION sequencing, the DNA was neither sheared nor size selected. The MinION library was prepared with 500 ng DNA using the ligation sequencing kit (SQK-LSK109; Oxford Nanopore Technologies, France) according to the manufacturer's instructions, and long-read sequencing was performed using a Flongle (R9. 4. 1) flow cell on the Oxford Nanopore MinION sequencer for 24 h. Default parameters were used for all software unless otherwise specified. The Illumina sequencing resulted in 8,856,638 raw reads, which were analyzed for quality control, normalization, and assembly using the ARTwork workflow  (5). The raw reads were normalized (100Â) using BBMap v38. 22 and BBNorm v36. 14  (6). The reads were trimmed (Phred score, 30Â; trailing,.
20; minimum length, 50 bp) using Trimmomatic v0. 33  (7)  and de novo assembled using SPAdes v3. 13. 0 (8) (minimum contig length, 200 bp), producing 15 contigs. The raw fast5 files produced by the MinION sequencing were base called using the ONT Guppy v4. 4. 2 base caller with high accuracy mode. The sequencing output was 55,329 reads. The quality of the MinION read files as determined using NanoPlot v1. 28. 2 (9) passed the standard quality checks with a mean read quality of 11. 0 and median read quality of 11. 7. The read length N 50 value was 20. 9 kbp. Hybrid assembly was performed using the Unicycler v0. 4. 8 assembler (  10 ), combining the sequence data sets generated by both Illumina and Oxford Nanopore Technologies sequencing. Unicycler default parameters were used, except -min_fasta_length 1000, to obtain a genome of 4,676,102 bp with a GC content of 52.
29%, divided into 3 circular contigs-the chromosome (4,667,486 bp) and two plasmids of 4,712 bp (GC content, 51. 10%; GenBank accession number CP073716. 1) and 3,904 bp (GC content, 51. 10%; CP073717. 1). Unicycler was used to circularize the replicons and search for dnaA or repA alleles. If such a sequence was found, the replicon as rotated so that it began with that gene encoded on the forward strand. S. Bovismorbificans was attributed using the SeqSero v1. 2 application on the Center for Genomic Epidemiology website (https://cge. cbs. dtu. dk/services), and the multilocus sequence type (ST) was found to be ST142. The sequence was annotated using the National Center for Biotechnology Information (NCBI) Prokaryotic Genome Annotation Pipeline (PGAP) at http://www. ncbi. nlm. nih. gov/genome/ annotation_prok.
Summary of molecular data Six of seven patients ascertained in this study are heterozygous for one of two missense mutations (p. (Gly355Asp); p. (Arg528Trp)) in ATAD3A (Fig. 1 A ), neither of which is recorded on publicly available databases, being absent from >250,000 control alleles on gnomAD. The substituted amino acids are highly evolutionarily conserved (Fig. 1 B ), and the amino acid substitutions are predicted as damaging by in silico algorithms (SIFT: Damaging; Polyphen2: Probably damaging). The glycine to aspartate substitution at amino acid 355 falls within the highly conserved Walker A motif, responsible for ATP binding in the AAA+-ATPase module of ATAD3A (Fig. 1C )  (Baudier, 2018). Importantly, recombinant p. (Gly355Asp) mutant ATAD3A protein was shown to be associated with a markedly reduced ATPase activity, and demonstrated a strong dominant-negative effect on the ATPase activity of wild-type protein  (Cooper et al.
Genetic studies DNA was extracted from whole blood using standard methods. Exome sequencing was performed on genomic DNA from Patients 1 and 2 and their parents using a SureSelect Human All Exon kit (Agilent Technologies) for targeted enrichment, and Illumina HiSeq2000 for sequencing. Variants were assessed using the in silico programs SIFT (http://sift. jcvi. org) and Polyphen2 (http://genetics. bwh. harvard. edu/pph2/). Population allele frequencies were obtained from the gnomAD database (http://gnomad. broadinstitute. org). Sanger sequencing was performed to confirm the identified ATAD3A variants. The reference sequence used for primer design and nucleotide numbering was NM_001170535.
Agilent Tapestation was used to assess the quality of the RNA. 100ng of total RNA was loaded for each sample. Data were processed with nSolver software (NanoString Technologies Seattle, WA). The data was normalized relative to the internal positive and negative calibrators, the 3 reference probes and the control samples. The median of the 24 probes for each of 27 healthy control samples was calculated. The mean NanoString score of the 27 healthy controls +2SD of the mean was calculated. Scores above this value (2. 75) were designated as positive.
15 NA. TMRE (530-560 nm), MitoTracker DeepRed (615-645nm), and DAPI (355-385 nm) were excited the appropriate LEDs (Operetta CLS). Harmony Analysis Software (PerkinElmer) was used for automated confocal image analysis as described in detail in  Cretin et al. (2021). Z-projected images first undergo brightfield correction. Nuclei and cellular segmentation were defined using the "Find Nuclei" building block with the HOECHST 33342 channel and the "Find Cytoplasm" building block with the Alexa 633 Mitotracker DeepRed (MTDR, mitochondria) channel. Mitochondrial network was analyzed using SER Texture properties (Ridge, Bright, Edge, Dark, Valley, Spot) and the PhenoLOGIC supervised machine learning algorithm was used to identify the best properties able to segregate the three populations: "Normal", "Fragmented" and "Hypertubulated" network.
Quantification and statistical analysis Statistical analysis was conducted using GraphPad Prism 8 software. Communication is limited to eye movements and facial expression. Her head circumference is on the 50 th centile, and cranial MRI showed some high signal in the anterior temporal lobes and at the parietal ventricular poles, with no obvious calcification. Patient 2: This female was noted to have an absence of the eyelashes and eyebrows, myopia, and early-onset alacrima in the first year of life. She required corneal grafts at age five years because of bilateral keratitis secondary to her alacrima. She subsequently developed features of autoimmunity including antibody-positive Hasimoto's thyroiditis and vitiligo, also demonstrating growth hormone deficiency. Mild lower limb spasticity was noted in infancy, prompting cerebral MRI at age 6 years and a CT one year later, which were both normal.
ACKNOWLEDGEMENTS YJC acknowledges that this project has received funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  (grant agreement No  786142 ), a state subsidy managed by the  National Research Agency (France)  under the 'Investments for the Future' program bearing the reference  ANR-10-IAHU-01 , and the  NIHR UK Rare Genetic Disease Research Consortium. The project was supported by  MSDAVENIR (Devo-Decode  Project). EVN acknowledges the  Research Foundation Flanders (Fonds voor Wetenschappelijk Onderzoek Vlaanderen : grant No. 1S22716N ). We sincerely thank  Jacques Baudier  for the generous use of antibodies. BC is a Senior Clinical Investigator of the  Research Foundation-Flanders. Ghent University Hospital, University Hospital Leuven, and Hôpital Universitaire Necker  are members of the European Reference Network on Skin disorders (ERN-Skin).
HSPC differentiation trajectory is associated with transcriptional programs that are altered upon aging Cell fate decision and proper function of HSCs rely on tightly controlled transcriptional programs orchestrated by transcription factor (TF) activity  [37]. Since level of the expression of TFs is not sufficient to assess their activity, we measured changes in TF activity during differentiation and aging of HSPCs. For that, we took advantage of Single-Cell Regulatory Network Inference and Clustering (SCENIC) approach  [38]  that calculates the activity of a given TF (regulon score) based on target expression and cis-regulatory elements. We considered 154 TFs, selected from the literature or from our single cell expression data analysis (Seurat cluster markers), out of which, 58 were identified as active regulons in our HSPCs (Additional file 10: Table  S9A ).
2, anti Sca-1, anti-cKit, anti CD150, anti Cd48, anti Cd34, and anti Flt3 antibodies (Additional file 12: Table  S11 ) to purify Lin-Sca1+cKit+ Flt3 cells (HSPCs) by multi-parameter fluorescenceactivated cell sorting (FACS) on a FACSAriaII (Specia-lOrderResearch Products; BD Biosciences). Flow cytometry analyses were performed using a BD-LSRII cytometer and analyzed using BD-DIVA Version 6. 1. 2 software (Special Order Research Products; BD Biosciences).
Single cell RNA-seq and data processing We used the 10x genomics platform from two facilities: HalioDX for samples Young_A and Old_A (Marseille, France) and TGML for samples Young_B and Old_B (Marseille, France). In both facilities, FACS purified HSPCs were loaded 30 min after the sorting onto a Chromium Single Cell Chip and processed with the Chromium Controller (10x Genomics) according to the manufacturer's instructions for single cell barcoding at a target capture rate of 4000 individual cells per sample. Libraries were prepared using Chromium Single-Cell 3′ Reagent Kits v2 (10x Genomics) and were sequenced using an Illumina NextSeq500 sequencer to an average depth of about 45,000 reads per cell for Young_A and Old_B samples and about 130,000 reads per cell for Old_A and Young_B samples.
Quality control and data normalization Cells outside 2 standard deviations (SDs) from the mean UMI log-counts were filtered out for each sample to discard poor quality cells and doublets. In total, 7433 young and 7482 aged cells were kept. For each dataset (our four samples and the Rodriguez-Fraticelli dataset), genes with no UMI count in more than 0. 5% of the cells were discarded. All gathering, 17,513 genes were kept. Then, UMI counts were normalized with the NormalizeData Seurat function. For each cell, we considered the log transformation of the ratio of UMI counts per gene by the total UMI counts of the cell, multiply by a scaling factor of 10,000 (log (10,000(UMI gene /UMI cell ) + 1)).
Cell cycle phase classification Prediction of cell cycle phase for each cell was made with the cyclone  [62] , which relies on a pre-defined classifier for cell division constructed from a training dataset of synchronized mouse embryonic stem cells  [63]. For each cell, a score based on raw count data before gene filtering was computed for each phase (G2/M, S and G1) and used to assign a phase to the cells. As quiescent HSCs are closer transcriptionally to G1 than S or G2/M cells of the cyclone training dataset, we classified them with the cyclone G1 cells and named this category G1/G0.