TFEB induces mitochondrial itaconate synthesis to suppress bacterial growth in macrophages

Successful elimination of bacteria in phagocytes occurs in the phago-lysosomal system, but also depends on mitochondrial pathways. Yet, how these two organelle systems communicate is largely unknown. Here we identify the lysosomal biogenesis factor transcription factor EB (TFEB) as regulator for phago-lysosome-mitochondria crosstalk in macrophages. By combining cellular imaging and metabolic profiling, we find that TFEB activation, in response to bacterial stimuli, promotes the transcription of aconitate decarboxylase (Acod1, Irg1) and synthesis of its product itaconate, a mitochondrial metabolite with antimicrobial activity. Activation of the TFEB–Irg1–itaconate signalling axis reduces the survival of the intravacuolar pathogen Salmonella enterica serovar Typhimurium. TFEB-driven itaconate is subsequently transferred via the Irg1-Rab32–BLOC3 system into the Salmonella-containing vacuole, thereby exposing the pathogen to elevated itaconate levels. By activating itaconate production, TFEB selectively restricts proliferating Salmonella, a bacterial subpopulation that normally escapes macrophage control, which contrasts TFEB’s role in autophagy-mediated pathogen degradation. Together, our data define a TFEB-driven metabolic pathway between phago-lysosomes and mitochondria that restrains Salmonella Typhimurium burden in macrophages in vitro and in vivo.

from the mitochondrial tricarboxylic acid (TCA) cycle in modulating inflammatory circuits and microbial control [8][9][10][11] . Although it is known that mitochondria can act synergistically and even interact physically with lysosomes in some cell types 12,13 , it remains largely unknown how these two organelle systems communicate or integrate their functions to control bacterial challenges [14][15][16] .
To identify pathways for potential inter-organellar communication between phago-lysosomes and mitochondria in macrophages, we began our study by modulating TFEB 2,17 . Previous work showed that TFEB is activated upon bacterial uptake via phago-lysosomal calcium release, and benefits bacterial clearance 18 . While TFEB is best known as regulator of lysosomal biogenesis 19 , it is emerging to control pleiotropic processes. The underlying mechanisms for its antimicrobial control remain largely unexplored 18 .
We confirmed that bacterial signals induce the nuclear translocation of TFEB in bone marrow-derived macrophages (BMDMs), including heat-killed Mycobacterium tuberculosis ( Fig. 1a and Extended Data Fig. 1a), living Salmonella Typhimurium ( Fig. 1b and Extended Data Fig. 1a), or the combined stimulation with lipopolysaccharides (LPS) and interferon-γ (IFNy) (Fig. 1c and Extended Data Fig. 1a). To identify TFEB-transcriptional targets in BMDMs, we used a retrovirally controlled TFEB-GFP overexpression system, which resulted in a twofold increase of cellular and nuclear TFEB levels relative to green-fluorescent protein-(GFP-) expressing control BMDMs (Extended Data Fig. 1b). Our observed nuclear TFEB increase was comparable to ranges reported for endogenous TFEB upon bacterial stimulation 20 . Using this activation mimic, we performed RNA-sequencing (RNA-seq) and assessed the biological processes enriched in upregulated genes (Fig. 1d,e). As expected, the top hit referred to changes in lysosomal biology ( Fig. 1d and Extended Data Fig. 1c), which was reflected in increased total lysosomal mass (Extended Data Fig. 1d). Ten out of the following 11 enriched gene categories were related to metabolic processes (Fig. 1d). In particular, we found genes relevant for cellular and mitochondrial glucose fuelling (Fig. 1e). This included genes Letters NATuRE METABOLISM encoding glucose transporters (Slc2a1, Slc2a6) and glycolytic enzymes (Aldoa, Hk1, Pfkl) (Fig. 1e, left panel), transcriptomic signatures that correlated with mildly elevated glycolysis in macrophages (Extended Data Fig. 1e) 21 . Most surprising, however, was the regulation of enzymes that fuel mitochondria with pyruvate (Pdha, Pcx) and genes that indicated a biosynthetically active TCA cycle (Slc25a1, Irg1, Idh3a) (Fig. 1e, right panel), a key process in activated macrophages 22 .
To analyse the mitochondrial TCA cycle in more detail, we followed the fate of mitochondria-imported carbon from glucose by metabolic labelling of macrophages with 13   . Dotted lines indicate cell nuclei. Scale bars, 10 µm. Images are representative of n = 2 independent experiments. d,e, Analysis of RNA-seq data. d, Top overrepresented biological processes among significantly upregulated genes from RNA-seq analysis of TFEB-GFP-relative to GFP-expressing naïve BMDMs. e, RNA-seq analysis of glucose metabolism and TCA-cycle genes that are significantly differentially expressed between TFEB-GFP-and GFP-expressing BMDMs. Data stem from n = 1 biological replicate with n = 3 technical replicates. f-h, Metabolic labelling of BMDMs with 13 C-glucose in the presence or absence of LPS/IFNγ for 6 h measured by GC-MS/MS. f, Results of 13 C fractional label of TCA-cycle metabolites. g, Quantification of 13 C-glucose fractional label lost between citrate and glutamate. h, 13 C-glucose label in itaconate and palmitate in naïve TFEB-GFP-and GFP-expressing BMDMs. g,h, Bars show mean ± s.d. of n = 3 independent biological replicates, P values were calculated using unpaired, two-sided Student's t-test (g) and one-way analysis of variance (ANOVA) with Tukey's post hoc test (h), NS P > 0.05. glu., glutamate, α-keto., alpha-ketoglutarate, veh., vehicle.

Letters
NATuRE METABOLISM 13 C-glucose-derived carbon into citrate than control cells ( Fig. 1f and Extended Data Fig. 1g). In contrast, TCA-cycle fuelling with 13 C-palmitate or 13 C-glutamine was not or less strongly increased upon TFEB activation (Extended Data Fig. 1g). The elevated 13 C-glucose label was not retained throughout the full TCA cycle (Fig. 1f,g) to fuel mitochondrial respiration (Extended Data Fig. 1f). Instead, a large portion of 13 C-label did not reach glutamate (a proxy for α-ketoglutarate) and further downstream metabolites (Fig. 1f,g). Citrate is a pivotal TCA-cycle intermediate and functions as precursor for the de novo synthesis of fatty acids and the TCA-accessory metabolite itaconate 22 (Fig. 1f). When we followed the fate of glucose-derived carbon downstream of citrate, we found that TFEB activation routed carbon flux primarily into itaconate, an integral metabolite of the pro-inflammatory macrophage response 23 , but not palmitate (Fig. 1h)

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that is normally engaged in macrophages upon bacterial stimulation (Extended Data Fig. 1h) 22 . Thus, our data reveal a previously unappreciated link between TFEB and a biosynthetic TCA-cycle state in macrophages. TFEB's altered carbon funnelling resulted in substantially elevated cellular itaconate levels (Fig. 2a), as measured by liquid chromatography coupled to mass spectrometry (LC-MS). Similar to the genetic model, the activation of endogenous TFEB by the TFEB activator (TFEBa) 2-hydroxypropyl-β-cyclodextrin 24 enhanced glucose-derived carbon fuelling of itaconate and increased itaconate levels ( Fig. 2b and Extended Data Fig. 2a,b). Itaconate production was also induced by TFEB activation after lysosomal inhibition via the V-ATPase inhibitor bafilomycin A1 (Baf) 25 (Fig. 2c and Extended Data Fig. 2a). Thus, TFEB activation alone is sufficient to produce itaconate without additional need for a pro-inflammatory macrophage signal.
Next, we examined the functional relationship between TFEB activation and itaconate production in macrophages challenged with bacterial stimuli. In control BMDMs, LPS/IFNγ stimulation caused peak levels of itaconate within the first 6 h of macrophage activation (Extended Data Fig. 2c). These peak levels were comparable to TFEB-induced itaconate levels in naïve macrophages (Fig. 2d, red rectangle). Additional activation of TFEB by LPS/IFNγ treatment or LPS signalling alone further augmented itaconate levels ( Fig. 2d and Extended Data Fig. 2d), without affecting iNOS expression, a negative regulator of itaconate synthesis in activated BMDMs (Extended Data Fig. 2e,f) [26][27][28] . Conversely to TFEB-activated cells, BMDMs that were genetically depleted of TFEB (Tfeb −/− ) (Extended Data Fig. 2g) were significantly impaired in itaconate synthesis in response to several heat-killed bacteria, including Staphylococcus aureus, M. tuberculosis and S. enterica serovar Typhimurium (Fig. 2e) and to LPS/IFNγ treatment (Fig. 2f). Thus, our data identify TFEB as a new driver of itaconate production during bacterial stimulation.
We also investigated the TFEB-itaconate pathway in macrophages from a murine model of the human immunodeficiency Chediak Higashi Syndrome (Souris). In this disorder, a key step for TFEB activation upon bacterial uptake, the maturation of the phago-lysosome, is disturbed 5,29 . Accordingly, we found that in diseased (Souris −/− ) macrophages nuclear TFEB translocation and itaconate synthesis were reduced relative to healthy macrophages (Souris +/− ) treated with bacterial particles (Fig. 2g-i). Together, our data identify TFEB as novel regulator of itaconate production and provide evidence that phago-lysosomal dynamics and lysosomal stress signalling control the production of the mitochondrial metabolite itaconate.
Two mechanisms were recently shown to promote Irg1 expression: type I interferon signalling and interferon regulatory factor 1 (IRF1) activation 31,32 . However, their roles for TFEB-driven Irg1 expression are unclear (Fig. 3d). We demonstrate that TFEB activation neither induced the expression of interferon β, nor did the loss of the interferon receptor (IFNAR1) suppress TFEB-driven Irg1 transcription (Fig. 3e,f). Similarly, TFEB was able to elevate Irg1 expression in BMDMs lacking IRF1, albeit total Irg1 mRNA levels were reduced (Fig. 3g). Thus, our data show that TFEB contains an inherent ability to increase Irg1 mRNA levels, which is additionally modulated by previously described type I interferon elements 26,27 . Beyond that, glycolysis 33 , mitochondrial pyruvate-import and the TFEB-target autophagy 34 (Extended Data Fig. 3e,f) were dispensable for Irg1 expression.
To address the possibility that TFEB directly engages Irg1 expression, we examined chromatin accessibility changes by assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq). Comparing our ATAC-and RNA-seq data showed that changes in chromatin accessibility correlated significantly with changes in gene expression (Extended Data Fig. 3g). Overall, we found 16,000 more accessible chromatin sites in TFEB-activated macrophages, including two sites in the promoter region of the Irg1 gene (Fig. 3h, (Fig. 3i, lower panel), suggesting that TFEB may directly target Irg1 transcription. Supporting this, chromatin immunoprecipitation-quantitative PCR (ChIP-qPCR) showed that TFEB binds to the Irg1 promoter at an element 800 bp upstream of the transcriptional start site (Extended Data Fig. 3h). This region, containing the TFEB-consensus motif, was also essential for nuclear TFEB-driven expression from the Irg1 promoter, as assayed by a luciferase-Irg1-promoter system (Extended Data Fig. 3i). Thus, our data support a model whereby TFEB directly induces Irg1 expression to enhance the production of the antimicrobial metabolite itaconate.
TFEB activation and itaconate synthesis have both individually been suggested to restrict the survival of several intracellular bacteria 18,35 (Extended Data Fig. 4a). However, these two cellular processes have only been viewed as separate pathways and were never functionally linked as part of a concerted antibacterial response. To address the functional role of the TFEB-Irg1-itaconate pathway for the survival of an intracellular bacterium, we infected macrophages with the food-borne facultative intracellular pathogen, S. enterica serovar Typhimurium. This itaconate-sensitive pathogen 23 was shown to escape TFEB control by inactivating the transcription factor shortly after infection 36 , which we confirmed by measurements of reduced cellular and nuclear TFEB levels ( Fig. 4a,b). Supporting that Salmonella efficiently restrict TFEB activity, itaconate levels were only mildly reduced in infected Tfeb −/− BMDMs (Extended Data Fig. 4b) and bacterial loads were comparable between WT and Tfeb-deficient macrophages in vitro and in vivo ( Fig. 4c and Extended Data Fig. 4c). In contrast, the TFEBa was able to overcome bacteria-induced TFEB repression: it raised cellular itaconate levels (Extended Data Fig. 4b) and lowered bacterial loads in macrophages in vitro and in vivo (Fig. 4c,d), corroborating beneficial effects of this treatment in Salmonella-infected mice 37 .
To understand in detail how the TFEB-itaconate pathway targets intracellular Salmonella survival, we made use of an established Salmonella fluorescence dilution system. This experimental system allows the distinction between different macrophage control mechanisms: the ability of the macrophage to (1) kill the pathogen and (2) restrict its escape into proliferating states 38 . For this, we infected macrophages with Salmonella that carried the fluorescence dilution-plasmid with constitutively expressed mCherry and conditionally expressed GFP, whose synthesis is terminated at the onset of infection (Fig. 4e). Proliferating bacteria display high mCherry to GFP signal intensity ( Fig. 4e and Extended Data Fig. 4d growing, red gate) and can be distinguished from non-proliferating bacteria (constant mCherry and GFP signals) ( Fig. 4e and Extended Data Fig. 4d, non-growing, black gate), early host-killed bacteria (mCherry-positive, but low GFP signal) ( Fig. 4e and Extended Data Fig. 4d host-killed, dashed gate) and later degradation stages that lose all fluorescence.
Using this fluorescence dilution assay, we found that pharmacological TFEB activation led to a specific and marked reduction of the proliferating Salmonella population ( Fig. 4f and Extended Letters NATuRE METABOLISM Data Fig. 4d), with milder or non-significant effects on the other two bacteria subsets (Extended Data Fig. 4d,e). A direct effect of TFEBa on Salmonella proliferation and survival could be ruled out, as this treatment did not reduce the in vitro growth of bacteria when cultured in complete or a minimal bacterial growth medium that mimics the vacuolar environment of macrophages 39 (Extended Data Fig. 4f). Also, the activation of the Salmonella pathogenicity island 2 (SPI-2) virulence programme, which is essential for  Bars show mean ± s.d. of n = 3 independent experiments. P values were calculated using one-way ANOVA, with Tukey's post hoc. h, Heatmap depicting differentially accessible regions in GFP-and TFEB-GFP-expressing BMDMs, using a window of ±3 kb from the centre of the peak (CoP). Three clusters are represented denoting the commonly (common) accessible sites and the regions that loose or gain accessibility upon TFEB expression (lost and gained, respectively). i, Representative gene tracks from ATAC-seq data of the Irg1 gene region. Blue boxes indicate significantly gained peaks in TFEB-GFP-relative to GFP-expressing BMDMs. The y axis represents the reads per kilobase of transcript per million of mapped reads. Potential TFEB binding sites, derived from motif analysis are highlighted. Data show n = 1 experiment with n = 2 technical repeats.

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intracellular bacterial proliferation 40 , was grossly unaffected by TFEBa treatment (Extended Data Fig. 4g). Instead, we found that the antiproliferative and bacterial load-reducing effect in macrophages upon TFEB re-activation was dependent on Irg1-driven itaconate synthesis, as shown by experiments in Irg1 −/− BMDMs and mice (Fig. 4f,g and Extended Data Fig. 4h). Moreover, ectopic Irg1 expression (Extended Data Fig. 4i) and extracellular addition of itaconate to infected macrophages (Extended Data Fig. 4j) both reduced the growing bacterial subset, corroborating the repressive effect of itaconate on Salmonella proliferation. Bacterial repression by the TFEB-itaconate axis was largely independent of autophagy, another TFEB-induced pathway 34,41 , as assessed in autophagy-deficient Atg7 −/− BMDMs (Extended Data Fig. 4k). Instead, autophagy contributed significantly to the early host-killed population in TFEBa-treated and control macrophages (Extended Data Fig. 4l), as suggested previously 37 . Thus, our data identify itaconate production as a new Atg7-independent TFEB-executor, selectively controlling the virulent subset of proliferating Salmonella. Itaconate can be transferred from mitochondria into the pathogen-containing vacuole via Irg1-Rab32-BLOC3-driven organelle interactions and directly inhibit Salmonella growth 9,23 (Extended Data Fig. 4a). To assess whether vacuolar itaconate mediates the growth suppressive TFEB-effect, we infected macrophages with Salmonella carrying previously described sensor plasmids (GFP-ITA or NanoLuc-ITA) that allow the visualization and measurement of vacuolar itaconate 9 ( Fig. 4h and Extended Data Fig. 5a). Although, Salmonella Typhimurium can partially counteract vacuolar itaconate transport by cleaving Rab32 (ref. 9 ) (Extended Data Fig. 5b), we found that TFEB activation increased the percentage of itaconate-exposed pathogens (Fig. 4h) and raised vacuolar itaconate levels by 2.6-fold in comparison to control cells (Fig. 4i,j). TFEB activation was accompanied by a mild, Irg1-dependent reduction in Rab32 cleavage and slightly increased mitochondria-pathogen colocalization (Extended Data Figs. 5b-e), supporting that Irg1 is part of the Rab32-BLOC3 itaconate-transfer system, as reported previously 9 . Genetic inactivation of the Rab32-BLOC3-transfer system (Hps4 −/− BMDMs) 9 repressed TFEB's ability to elevate vacuolar itaconate and decreased itaconate to similar levels found in Hps4 −/− control cells (Fig. 4i,j). This supports that TFEB depends on active Rab32-BLOC3 sites to increase vacuolar itaconate levels.
To assess in depth the influence of vacuolar itaconate transfer on bacterial proliferation in macrophage populations, we quantified the bacterial load per cell by single cell imaging (Extended Data Fig. 5f,g). TFEB-itaconate activation in WT BMDMs specifically targeted macrophages with high bacterial burden and lowered the number of proliferating bacteria in these cells ( Fig. 4k and Extended Data Fig. 5f,g). In striking contrast, TFEB activation in Hps4 −/− cells failed to restrain bacterial proliferation ( Fig. 4k and Extended Data Fig. 5f,g), which was also mirrored by an increase in bacterial colony-forming units (CFUs) (Fig. 4l). Thus, our data indicate that TFEB elevates itaconate synthesis upon which the metabolite is transferred into the vacuole in a Rab32 or Hps4-dependent manner to inhibit pathogen proliferation.
Our findings expand the function of TFEB beyond its established regulatory roles for lysosome biology and autophagy 34 . While TFEB has been linked to the control of metabolic functions in non-immune cells 41,42 , the TFEB-Irg1-itaconate pathway has remained undetected, probably due to the restricted expression of Irg1 by only few cell types 43,44 . In primary macrophages, our results identify the TFEB-driven Irg1-itaconate axis as a lysosome-to-mitochondria communication pathway that controls a cell-autonomous antibacterial defence mechanism to protect the phago-lysosomal compartment from being exploited as bacterial proliferation niche. Our data indicate that the TFEB-Irg1-itaconate pathway exerts its antimicrobial function primarily in the vacuole: functions of cytosolic itaconate 45,46 , TFEB or Hps4, and potential functional interactions between those systems 47 , may play additional roles or modulate the vacuolar response 48 . How itaconate controls Salmonella proliferation mechanistically is currently unclear, but probably relates to its ability to inhibit selected metabolic enzymes. This includes key enzymes in the glyoxylate shunt and propionate metabolism that different pathogens rely on for intra-macrophage growth during acute and chronic infections 23,35,[49][50][51] . Given the reported reduced itaconate synthesis in human macrophages 4 , it remains to be determined whether the TFEB-Irg1-itaconate pathway also holds promise to target virulent infections with Salmonella Typhimurium, or other itaconate-sensitive microbes such as S. Typhi and Mycobacterium spp. 9,35 in humans. Beyond its antimicrobial activity itaconate is also known as an immunomodulatory metabolite 45,52 . Thus, one could speculate that some of TFEB's reported anti-inflammatory and immunomodulatory effects may act through control of itaconate 18,53 . In vivo infection studies of 12-25-week-old female and male mice (Fig. 4d,g and Extended Data Fig. 4c,d) were infected intra-peritoneally with 5 × 10 4 CFU per mouse of S. Typhimurium SL1344 with arabinose-induced pFCcGi-Cb. Animals were kept for 3 days and TFEBa (0017; Acacetin, Sigma Aldrich) dissolved in PBS (20 mg kg −1 , sonicated for 5 min) or relevant solvent (PBS) was injected daily. For Tfeb-deletion studies, mice with macrophage-specific Tfeb knockout were used (Tfeb fl/fl Lyz2-Cre), annotated as Tfeb Δmac . Mice were euthanized by CO 2 and cervical dislocation and spleens were harvested. Cell suspensions were obtained by homogenizing the spleens using 70-μm cell strainers. Erythrocyte lysis (ACK lysing buffer, Gibco A1049201) was performed and unspecific binding was blocked with anti-CD16/32 for 15 min before cells were stained for F4/80 (1:200 Retrovirus. pBMN-TFEB-GFP and ΔNLS-TFEB-GFP plasmids were kind gifts from R. Youle and S. Ferguson, respectively 54,55 . The pBMN-Irg1-BFP plasmid was generated by replacing the Tfeb gene in pBMN-TFEB-GFP plasmid with the Irg1 sequence from the pCMV6-Entry-Irg1-Myc-DDK-tagged plasmid purchased from Origene and the GFP was replaced by the blue fluorescent protein (BFP) sequence. New plasmids were generated using the CloneAmp HiFi PCR Premix and In-Fusion HD Cloning Kit (Takara) according to the manufacturer's instructions. For production of viral particles, 2.5 × 10 6 PlatE cells were plated and the following day transfected with pBMN-plasmid DNA using Lipofectamine 3000 according to the manufacturer's instructions. Viral supernatant was collected every 24 h for 4 days. RNA-seq. RNA isolation was performed using the RNeasy MinElute Cleanup Kit according to the manufacturer's instructions. Complementary DNA libraries were prepared by the Deep Sequencing facility at the Max Planck Institute of Immunobiology and Epigenetics using the TrueSeq stranded mRNA protocol (Illumina) and sequenced on a HiSeq 3000 (Illumina) platform to a depth of 16 million reads per sample. Sequencing data were analysed using the Galaxy platform provided by the Bioinformatics Core Facility of the Max Planck Institute of Immunobiology and Epigenetics and the University of Freiburg. The STAR aligner 56 was used for trimming and mapping, GRCm38 as the reference genome. Quantification of the mapped reads was performed with featureCounts 57 (https://doi.org/10.1093/bioinformatics/btt656) and differential gene expression determined using the DESeq2 algorithm 58 (https://doi.org/10.1186/s13059-014-0550-8). Expression data were further processed and filtered using R (Lucent Technologies). For biological pathway enrichment analysis, significantly upregulated genes (adjusted P ≤ 0.01) in TFEB-GFP-versus GFP-expressing BMDMs were subjected to the PANTHER classification system v.13 (http://www. pantherdb.org) using the Gene List analysis (Statistical overrepresentation test, Annotation Data Set, PANTHER GO-Slim Biological Process; Reference List, Default Mus musculus genes) to define overrepresented biological processes.

Methods
ATAC-seq. BMDMs were collected with 0.25% trypsin and 50,000 BMDMs per sample were lysed in ice-cold lysis buffer (10 mM Tris-Cl, 10 mM NaCl, 3 mM MgCl 2 , 0.1% (v/v) Igepal CA-630, pH 7.4), immediately followed by centrifugation at 500g, 4 °C. Pellets containing BMDM nuclei were subjected to transposition reaction using the Nextera DNA Flex Library Prep Kit (Illumina). DNA libraries were sequenced in paired-end mode (75 cycles) on a HiSeq 3000 (Illumina) by the Deep Sequencing facility at the Max Planck Institute of Immunobiology and Epigenetics with a reading depth of 50 million reads per sample in two biological replicates per condition. ATAC-seq was run in two replicates per condition. Adapter sequences were trimmed with Trimmomatic (v.0.36) 59 and the Bowtie2 (ref. 60 ) algorithm (v.2.1.0) using the «-very-sensitive» parameter for aligning ATAC-seq reads to the mouse genome version GRCm38/mm10. Samtools 61 (v.0.1.19) were used for data filtering and file format conversion. Duplicate reads and chr M were removed before peak calling. MACS2 (ref. 62 ) (v.2.1.0) algorithm was used for ATAC-seq peak identification with a P value cut-off of 1 × 10 3 . Genomic regions that are common or different from a set of peak files were identified with BEDTools 63 (v.v.2.25.0). All .bam files were converted to bedgraphs with genomeCoverageBed a subcommand of BEDTools 63 . Gene annotation (100 kb upstream and 50 kb downstream from the transcription start site) and genomic distribution of accessible regions identified by MACS2 (ref. 62 ) were performed with BEDTools 63 and -closetBed and -intersectBed subcommands, respectively. Clustering of regions was generated with ComputeMatrix function of DeepTools 64 , using reference-point-referencePoint centre -b 3000 -a 3000 -R<bed files>-S<bigwig files> as parameters. The function plotHeatmap from the same package was used for displaying the average profiles heatmap. Differentially accessible chromatin regions were scanned for enriched short-sequence motifs using HOMER 65 software with the 'findMotifsGenome.pl' command. To search for a set of sequences for occurrences of specific known motifs FIMO 66 from the MEME suite 67 was used. For the Irg1 gene a window of 1 kb upstream and downstream from the start and end of the two significant gained narrow peaks was analysed with BEDTools 5 subcommand -slopBed -b 1000 and motif occurrences with a P value of less than 0.0001 were chosen.
ChIP. ChIP was performed as previously described 68 . Briefly, for each ChIP experiment 8-10 million cells were cross-linked with 1% formaldehyde (Pierce) for 10 min at room temperature, nuclei were isolated and chromatin was sonicated at 4 °C using a Bioruptor (Diagenode) for 25 cycles (30 s 'ON' and 30 s 'OFF' , power setting high). For each immunoprecipitation 18 μl of antibody against TFEB (Cell Signaling, no. 37785, D2O7D) were incubated with chromatin at 4 °C with rotation overnight. Chromatin was washed, crosslink was reversed at 65 °C overnight and DNA was isolated using Agencourt AMPure magnetic beads (Beckman Coulter). Subsequently, qPCR was performed (StepOne, Applied Biosystems) using ChIP and input DNA amplifying different regions around the transcriptional start site of Acod1 (Irg1). Enrichment of TFEB binding was calculated as ChIP-DNA relative to input-DNA PCR signal for each primer pair and normalized to a negative control region (non-accessible heterochromatin region).

Lysosomal mass measurements. BMDMs were incubated with 75 nM LysoTracker
Red for 30 min at 37 °C in BMDM medium. Cells were washed three times with prewarmed BMDM culture medium, gathered with 20 mM EDTA and incubated for 15 min on ice with Live Dead Fixable Viability eFluor 780 (1:1,000) in PBS. Samples were measured on the BD LSR Fortessa cell analyser (BD Biosciences). Data were analysed and graphs generated in FlowJo v.10.
Real-time qPCR. BMDMs were gathered in 250 µl TriReagent per well and RNA was isolated by phenol-chloroform extraction. cDNA synthesis was performed with the QuantiTect Reverse Transcription Kit according to the manufacturer's instructions. As template, 200 ng of RNA were used. The reverse transcription reaction was performed for 30 min at 42 °C. Measurement of Irg1, Tfeb, β-actin and β 2 -microglobulin mRNA expression was carried out in a 96-well plate using the Thermo Scientific ABsolute Blue QPCR SYBR Green Low ROX Mix according to the manufacturer's instructions using 1 µl of cDNA and 22 ng of the respective primers. Samples were measured in the 7500 Fast Real-Time PCR System (Applied Bioscience) and analysed via StepOne Software (AB, v.2.0). To quantify relative Irg1 mRNA expression, Irg1 mRNA levels were normalized to the expression of the housekeeping genes β-actin and β 2 -microglobulin. Relative mRNA expression values were calculated using the 2(-ΔΔCT) method and normalized to unstimulated control samples. For Fig. 3g and Extended Fig. 3d (2-DG treatment), Irg1 expression levels were normalized to Tfeb expression levels per sample because the genotype of the cells or the treatment affected Tfeb expression levels.
Seahorse flux analysis. Extracellular acidification rate and oxygen consumption rate were determined with a Seahorse Flux Analyser XF96 (Agilent Technologies) from GFP-or TFEB-GFP-expressing BMDMs. Seahorse XF base medium was supplemented with 25 mM glucose, 2 mM glutamine, 1 mM sodium pyruvate and 1% FCS. Seahorse measurements were normalized to protein content, determined with the Pierce BCA Protein Assay Kit or cell numbers by using in situ Hoechst staining of nuclei. Nuclear stainings were acquired with the BioTek Cytation 1/5. Nuclei counting was performed with the Seahorse XF and Cell Counting Software and the Wave v.2.6 Software (Agilent Technologies). Oxygen consumption rate data were calculated as area under the curve and values were plotted using GraphPad Prism v.8.2.1.

Metabolic tracing.
Metabolic tracing with 13 C -glucose, 13 C-glutamine and 13 C-palmitate was performed with gas chromatography coupled to tandem mass spectrometry (GC-MS/MS). For glucose and glutamine tracing, BMDMs were incubated for 6 h in glucose-or glutamine-free BMDM medium supplemented with 11 mM 13 C-glucose or 4 mM 13 C -glutamine, respectively. For palmitate tracing, full BMDM medium containing 20 µM BSA-conjugated 13 C-palmitic acid was used, as BMDMs were dying in lipid-deprived medium. To extract metabolites, BMDMs were washed once with ice-cold 0.9% NaCl in MilliQ-H 2 O,

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shock frozen in an ethanol-dry ice bath and collected with a cell lifter in ice-cold 80% methanol containing 1 µg ml −1 norvaline and 1 µg ml −1 adipic acid (internal standards). Cell debris was removed by centrifugation for 5 min at 20,000g and 4 °C. Methanol supernatants were collected and dried in a Genevac EZ-2 (SP Scientific). Metabolites were resuspended in 10 µl D27/methoxyamine mix (10 mg ml −1 methoxyamine hydrochloride, 0.2 µg ml −1 myristic-D 27 acid in pyridine) for 1 h at 30 °C. Then 7.5 µl of the mix were derivatized with 15 µl of N-(tert-butyldimethylsilyl)-N-methyl-trifluoroacetamid, with 1% tert-butyldimethyl-chlorosilane (375934 Sigma Aldrich) for 60 min at 80 °C. Isotopomer distributions were measured using a DB5-MS GC column in a 7890 GC system (Agilent Technologies) combined with a 5977 MS system (Agilent Technologies). Data from tracing experiments are presented as 13 C-labelled metabolite fractions of total respective metabolite level. Intracellular itaconate measurements. Polar metabolome quantifications were performed with LC-MS. BMDMs were stimulated as indicated. For metabolite extraction, cells were washed once with ice-cold 3% glycerol in MilliQ-H 2 O, followed by 5 min incubation on ice in prechilled 80% methanol. Methanol supernatants were collected and cell debris was removed by centrifugation for 5 min at 15,000g and 4 °C. Metabolite solutions were dried in a Genevac EZ-2 (SP Scientific) and subsequently resuspended in 15 µl of 90% acetonitrile containing 13 C-yeast-standard (ISOtopic Solutions) as loading control. Suspensions were centrifuged for 10 min at 3,300g and 4 °C and 10 µl of each sample were transferred to a fresh container and used for mass spectrometry. Targeted metabolite quantification by LC-MS was carried out using an Agilent 1290 Infinity II UHPLC in line with an Agilent 6495 triple quadrupole-MS operating in MRM mode. MRM settings were optimized separately for all compounds using pure standards. LC separation was on a Phenomenex Luna propylamine column (50 × 2 mm, 3-μm particles), with, a solvent gradient of 100% buffer B (5 mM ammonium carbonate in 90% acetonitrile) to 90% buffer A (10 mM NH 4 in water). Flow rate was from 1,000 to 750 µl min −1 . Autosampler temperature was 5 °C and injection volume 2 µl. Values represent the area of the metabolite peaks from mass spectrometry as arbitrary units.
Western blotting. BMDMs were collected in ice-cold PBS with a cell lifter and pelleted by centrifugation for 5 min at 500g and 4 °C. Cell pellets were lysed for 15 min on ice with lysis buffer (50 mM Tris, 150 mM NaCl, 0.1% Triton X-100, pH 7.4) with 1× Halt Protease Inhibitor Cocktail and 1× Phosphatase Inhibitor Cocktail and sheared with a 26 G insulin syringe. Cell debris was removed by centrifugation at 16,000g and 4 °C for 15 min. Then 25 to 35 µg of total protein was loaded on a 10 or 12% polyacrylamide gels. Protein transfer to a polyvinyl difluoride-membrane (Merck Millipore) was performed in a semidry blotting chamber for 90 min at 10 V. Membranes were blocked for 1 h in 5% milk in tris-buffered saline (TBS) with 0.1% Tween (TBST) at room temperature. Incubation with primary antibodies was performed overnight at 4 °C in buffers suggested for the specific antibody or in TBST containing 2% BSA. Incubation with secondary antibodies was performed for 1 h at room temperature in 5% milk in TBST. For signal detection, Amersham ECL Prime Western Blotting Detection Reagent was used and signals were acquired with the ChemiDoc Touch Gel Imaging System (Bio-Rad). Images were prepared for publication with the Image Lab v.5.2 TM Touch Software (Bio-Rad, v.1.0.0.15).
Immunofluorescence. BMDMs were plated in tissue culture treated 24-well plates containing fibronectin-coated 12 mm glass coverslips. To visualize TFEB, HSP60 or Salmonella, BMDMs were fixed for 15 min at room temperature in 4% paraformaldehyde, prewarmed to 37 °C, followed by permeabilization in 0.2% Triton X-100 in PBS. To visualize endogenous Irg1, BMDMs were fixed and permeabilized in ice-cold 100% methanol for 15 min at −20 °C. In both cases, unspecific binding sites were blocked afterwards for 1 h at room temperature in blocking buffer (0.1% Tween20, 5% FCS in PBS). Cells were incubated at 4 °C for 16 h with primary antibodies in blocking buffer. Secondary antibody stainings were performed in blocking buffer for 1 h at room temperature. BMDMs were mounted in Fluoromount-G supplemented with or without 4,6-diamidino-2-phenylindole (DAPI).
Confocal microscopy and image processing. Z-stacks were acquired with an inverted LSM880 or LSM780 Zeiss confocal microscope and ZEN software black edition (Carl Zeiss Microscopy, v.2.6). Brightness and contrast were adjusted and images prepared using Fiji ImageJ 69,70 . 3D-rendered images of mitochondria-pathogen interactions were generated using the surface tool of Imaris v.9.5.1 (Bitplane). For better visualization of differences in expression levels, Irg1 and Salmonella-mCherry fluorescent signals in Fig. 3b and Extended Fig. 4j were pseudocolored in ImageJ using the look-up table 'red hot' .

Image analysis.
To quantify nuclear TFEB-signals 3D nuclear masks generated from DAPI signal were generated, using the Imaris v.9.4.1 (Bitplane) surface tool (smoothing 0.51, signal intensities were set manually for each image). To quantify cellular TFEB levels in TFEB-GFP-or GFP-expressing BMDMs, cellular masks were generated on the basis of ectopically expressed GFP signals, as described for nuclear TFEB levels.
To determine the bacterial load of individual macrophages by imaging (Extended Data Figure 5f,g), maximum intensity projections of images taken from Salmonella-mCherry infected BMDMs were transformed to binary images and signal per cell were measured using the ImageJ analysis tool 69,70 . Measured signals were presented as frequency distributions in Extended Data Fig. 5g. Data were normalized for bacterial signals in TFEBa relative to vehicle-treated BMDMs for each independent experiment. The proliferating Salmonella subpopulation was determined on the basis of signal representing >15 bacteria per cell. Signals containing the growing Salmonella subpopulation (from bins [10][11][12][13][14] were summarized for vehicle and TFEBa-treated BMDMs for each genotype and depicted as ratio TFEBa/vehicle-treated in Fig. 4k.

Analysis of Salmonella subpopulations by flow cytometry.
To determine intracellular Salmonella subpopulations (growing, non-growing, host-killed) infected BMDMs were washed once with cold PBS and then collected on ice with a cell lifter in PBS. Per condition, three technical replicates were pooled. To assess Salmonella subpopulations on the basis of GFP and mCherry signals, samples were measured on a BD FACSAria III cell sorter with FACSDiva (BD, v.8.0.1). Control gates were set on the basis of there being uninfected or 30-min infected BMDMs (Extended Data Fig. 4d).
Luciferase assays. NanoLuc-ITA-Salmonella-infected BMDMs were lysed 18.5 h post-infection in Passive Lysis Buffer (E1941, Promega) and luciferase activity was determined using the Nano-Glo-Luciferase Assay System (N1110, Promega) according to the manufacturer's instructions and a Centro LB 963 Microplate Luminometer (Berthold). In parallel, CFUs were determined and luminescence values were normalized to the ratio of CFUs between TFEBa-treated and control BMDMs. For Irg1-promotor luciferase measurements, mouse embryonic fibroblasts (ATCC CRL-2907) were cotransfected with the indicated Irg1-promoter-firefly luciferase constructs and GFP as control or the indicated TFEB-GFP constructs. Then 24 h after transfection, cells were treated with medium or hk SmT (10 5 particles per ml) for 3 h and luciferase expression was measured using the Glo-Luciferase Kit (Promega) according to the manufacturer's instructions on a Centro LB 963 Microplate Luminometer (Berthold). Luciferase-expression levels were quantified as fold increase relative to Irg1-promoter-luciferase/GFP-coexpressing control cells.
Bacterial SPI-2 expression measurements. BMDMs were infected with Salmonella Typhimurium strain SL1344 carrying the P ssaG::gfp plasmid 71 , encoding a GFP-reporter gene under the control of the bona fide SPI-2 promotor of the ssaG gene. Bacteria were grown overnight in LB medium containing 50 µg ml −1 chloramphenicol. Opsonization and BMDM infection were performed as described in the Salmonella infection assay. To assess SPI-2 GFP-reporter expression, BMDMs infected for 18.5 h were fixed at room temperature for 15 min in 4% paraformaldehyde before being measured on a BD LSR Fortessa cell analyser (BD Biosciences), with FACSDiva (BD, v.8.0.1). FACS data were analysed with FlowJo v.10 software.

Quantification and statistical analysis. (Statistical analysis and data representation).
Graphs were generated and statistical analysis was carried out with GraphPad Prism v.8.2.1. To determine statistical significance, different tests were used as indicated in the figure legends. The number of experimental repeats is indicated in the figure legends. Proportional Venn diagrams for overlapping genes were generated with BioVenn 72 . Statistical significance of the overlap between the two groups of genes was calculated with a hypergeometric statistical test. Heatmaps were generated with Morpheus (Broad Institute) and schematics and figures with Adobe Illustrator CS5 (Adobe). Gene tracks of the Irg1 locus were generated with the Integrative Genomics Viewer (IGV) 73 .

Materials availability.
No new, unique reagents, plasmids or mice were generated in this study. A Material Transfer Agreement exists for the use of Tfeb flf/fl mice. These mice can only be shared via A.Ballabio.
Reporting summary. Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability
RNA-and ATAC-seq data generated in this study have been deposited at Sequence Read Archive with the accession code PRJNA647627. The authors declare that all other data supporting the findings of this study are available within the paper and supplementary information files. Source data are provided with this paper.

NATuRE METABOLISM
Extended Data Fig. 3 | TFEB activation drives irg1 expression independent of its metabolic targets and autophagy. a, Temporal correlation of Irg1 mRNA expression from qRT-PCR (red) and nuclear TFEB levels from immunofluorescence imaging (blue) in BMDMs stimulated with LPS/IFNγ. Line curves show mean of n = 1 independent experiment. b, Irg1 mRNA expression in naïve Tfeb −/− BMDMs, expressing TFEB-GFP, GFP or ΔNLS-TFEB-GFP. Graph shows mean ± s.d. of n = 3 independent experiments. P values were calculated using one-way ANOVA with Tukey's post-hoc, n.s. P > 0.05. c, Itaconate levels measured by LC-MS in GFP-or ΔNLS TFEB-GFP-expressing BMDMs. Bar shows mean of n = 3 independent experiments. P values were calculated using unpaired, two-sided Student's t-test. n.s. for P > 0.05. d, Irg1 mRNA expression in Tfeb −/− and WT BMDMs treated for 6 h with LPS/IFNγ. Graphs show mean ± s.d. of n = 5 independent experiments. P values were calculated using two-tailed, one-sample t-test. e,f, Irg1 mRNA expression in naïve TFEB-GFPexpressing BMDMs treated with vehicle, (e) 4 µM UK5099, 10 mM 2-DG, or (f) 10 mM 3-MA for 24 h. Graphs show mean ± s.d. of n = 3 independent experiments. P values were calculated using (e) one-way ANOVA with Tukey's post-hoc and (f) two-tailed, one-sample t-test. n.s. for P > 0.05. g, Venn diagram depicting differentially expressed genes (p ≤ 0.01) from RNA-seq analysis (blue) from Fig. 1d, or genes annotated to differentially accessible chromatin regions from ATAC-seq (green) n = 1 independent experiment with N = 2 replicates and the intersections of these data sets in naïve TFEB-GFPversus GFP-expressing BMDMs. Significance of overlap was calculated with hypergeometric statistical test. h, ChIP-qPCR of iBMDMs stably expressing human TFEB-GFP treated with or without heat-killed SmT (10 5 particles / mL) for 90 min. Bars show mean ± s.e.m. from n = 4 independent biological experiments. P values were calculated using one-way ANOVA with Tukey's post-hoc. n.s. for P > 0.05. i, Mouse embryonic fibroblast expressing the indicated TFEB and Irg1-promoter-Luciferase constructs were incubated with medium or heat-killed SmT (10 5 particles / mL) for 3 h and fold induction of firefly luciferase levels (RLU) was determined in TFEB/Irg1-promoter vs. GFP/Irg1-promoter expressing cells. Bar shows mean ± s.e.m. of n = 5 independent experiments. Pvalues were calculated using one-way Welch's ANOVA with Dunnett's post hoc. n.s. for P > 0.05.

NATuRE METABOLISM
Extended Data Fig. 4 | TFEB drives itaconate synthesis in infected macrophages to restrain intracellular Salmonella proliferation. a, Salmonella growth measured in OD 600 , in the presence of increasing itaconate concentration. Data show mean ± s.e.m. from n = 3 independent biological experiments. P values of the 8 h time points were calculated using one-way ANOVA with Dunnett's post-hoc. b, Ratios of cellular itaconate of Tfeb −/− to WT or TFEBa-to vehicletreated BMDMs. Bars show mean of n = 3 independent biological experiments. P values were calculated using two-tailed one-sample t-test, n.s. P > 0.05. c, Percentage of infected macrophages in spleens of Tfeb ΔMac or control mice, three days after i.p. Salmonella infection. Bar shows mean of n = 4 mice. P values were calculated using unpaired, two-sided Student's t-test. n.s. with P > 0.05. d,e, Flow cytometry analysis of Salmonella subpopulations upon TFEBa-or vehicle-treatment for 18.5 h in WT or Irg1 −/− BMDMs. (e) Quantification of (d). Graphs show mean from n = 6 independent experiments. P values were calculated using one-way ANOVA with Tukey's post-hoc. n.s. for P > 0.05. f, CFUs of Salmonella grown in vitro in LB or minimal medium for 18.5 h with or without TFEBa. CFUs are shown as ratio of TFEBa-to vehicle-treated control samples. Bar graphs show mean ± s.d. of n = 5 (LB) and n = 3 (minimal) independent experiments. P values were calculated using two-tailed one-sample t-test. n.s. for P > 0.05. Dashed lines indicate respective vehicle-treated control cells. g, SPI-2-activation assayed by flow cytometry. BMDMs infected with Salmonella carrying a SPI-2-GFP-reporter and treated with or without TFEBa. Bar graphs show mean percentage of GFP-positive BMDMs from n = 5 independent biological repeats. P values were calculated using one-way ANOVA with Tukey's post-hoc, n.s. P > 0.05. h, Flow cytometry of Salmonella-mCherry-containing splenic macrophages of WT or Irg1 −/− mice i.p. infected and treated with TFEBa or PBS. Plots are representative of n = 3 mice. i, Ratios of Salmonella subpopulations in Irg1-BFP-relative to BFPexpressing BMDMs. Bars show mean from n = 3 independent experiments. P values were calculated using two-tailed one-sample t-test. n.s. for p > 0.05. j, Bacterial load in Salmonella-infected BMDMs treated with exogenous itaconate for 18.5 h. Images are representative of n = 3 independent experiments. Scale bar: 50 µm. k,l, Percentage of BMDMs containing (k) growing or (l) early host-killed Salmonella in WT and autophagy-deficient Atg7 −/− BMDMs, treated with TFEBa or vehicle. Data represent mean of n = 6 (veh) and n = 5 (TFEBa) independent experiments. P values were calculated using one-way ANOVA with Tukey's post-hoc, n.s. for P > 0.05.  For metabolomics analysis: data sets were excluded when control cells (e.g. LPS/IFNg-treatment) failed to upregulate itaconate. For image analysis: Cells were excluded when poor staining qualities did not allow image acquisition or analysis. Also cells that overlapped with one another were excluded. For FACS analysis: In cases where control conditions did not show growing Salmonella populations, or where bacterial loads of splenic macrophages did not exceed levels found in non-infected control animals, these data sets were not used for further analysis.

Letters
Reproducibility of the experimental findings was verified using biological replicates and independent experiments. The numbers are indicated in the respective figures (individual data points). In addition, the majority of our Salmonella-infected studies were performed in two labs (Alexander Westermann and Rambold lab), and thus have been replicated by independent laboratories.
For experiments performed on cells, mice were randomly assigned. Animals ordered from the breeding facility were assigned to cages by the facility staff without knowledge of the experimental setup for which the mice were intended. The cages were randomly assigned to treatments.Experimental groups are defined by the genotype or treatments.
Experimentalists were blinded regarding BMDMs genotype. Mouse numbers were used as identifiers. Image acquisition and FACS analysis and metabolic measurements and analysis were performed blinded.
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