br Total ATP Glucose Uptake and
Total ATP, Glucose Uptake and Lactate Secretion
Glucose uptake and total ATP were measured on cells seeded in white 96-well plates (5000 cells/well) (Glucose uptake-Glo J1342, Cell-Titer-Glo, G7571, Promega). Extracellular lactate secretion was measured by collecting medium from 5000 cells cultured for 24 hr in 96-well plates. Harvested medium was diluted in PBS (1:50), and lactate content was determined with the Lactate-Glo assay (J5021, Promega) using 10 mL of diluted supernatant. Cells remaining in the 96-well plates were used to normalize the data.
RNA-Sequencing and Bioinformatics
Total RNAs were extracted with the RNeasy Plus Mini kit (74136, QIAGEN). Sequencing was done with an Illumina HiSeq PE150 instrument and Promega Relia-Prep. Paired end reads were obtained, and their quality score was determined with FASTQC. Sequencing reads were mapped to the GRCm38/mm10 mouse genome assembly with STAR Aligner (version 2.5.0a) (Dobin
et al., 2013), and genes were quantified with the HTSeq-count tool (version 0.6.1) (Anders et al., 2015). Tests for differential expres-sion of genes identified in RNA-seq analyses were done with DESeq2 (Love et al., 2014). Differentially expressed genes with a false-discovery rate < 0.05 were considered statistically significant. R Bioconductor package clusterProfiler was used for enrichment analyses (Yu et al., 2012).
Putative promoter regions 1000 bp upstream of each differentially regulated gene (n = 1025) were successfully extracted for 961 genes. Both Mus musculus BACH1 and NRF2 binding motifs were downloaded from JASPAR database of transcription factor bind-ing profiles by using R package MotifDb. Sequences 1000 bp upstream of genes were matched by the position-weighted matrix method using a multinomial model with a Dirichlet conjugate before calculation of estimated probability of Pam3CSK4 b at the position. The threshold of matching was set to 75%. Details about the method have been described (Bioconductor Maintainer at https:// bioconductor.org/packages/devel/workflows/vignettes/generegulation/inst/doc/generegulation.html). The SEEK database (http:// seek.princeton.edu) was interrogated to retrieve genes co-expressed with BACH1 in human lung cancer datasets (173 datasets). TGCA data were downloaded from http://www.cbioportal.org/. STRING analysis was done at https://version-10-5.string-db.org/ (version 10.5) using default settings, medium confidence (0.400), and four clusters.
Real-Time Quantitative PCR
Chromatin Immunoprecipitation-Sequencing (ChIP-Seq)
Lung tumor mTC and mTN cells (n = 3 biological replicates per condition) were fixed with 1% formaldehyde for 15 min and quenched with 0.125 M glycine. Chromatin was isolated by adding lysis buffer, and the cells were disrupted with a Dounce homogenizer. Lysates were sonicated, and the DNA was sheared to an average length of 300–500 bp. Genomic DNA (input) was prepared by incubating chromatin aliquots with RNase and proteinase K, heated for de-crosslinking, and precipitated with ethanol. Pellets were resuspended, and the resulting DNA was quantified with a NanoDrop spectrophotometer. Extrapolation to the original chro-matin volume allowed quantitation of the total chromatin yield. An aliquot of chromatin (30 mg) was pre-cleared with protein G agarose beads (Life Technologies). Genomic DNA regions of interest were isolated with 4 mg of antibody recognizing BACH1 (AF577, R&D Systems). Complexes were washed, eluted from the beads with sodium dodecyl sulfate buffer, and incubated with RNase and proteinase K. Crosslinks were reversed by incubation overnight at 65 C, and ChIP DNA was purified by phenol-chloroform extraction and ethanol precipitation.
Illumina sequencing libraries were prepared from the ChIP and input DNAs by the standard consecutive enzymatic steps of end-polishing, dA addition, and adaptor ligation. After a final PCR amplification step, the resulting DNA libraries were quantified and sequenced with an Illumina NextSeq 500 (75-nt reads, single end). Reads were aligned to the mouse genome (mm10) with the BWA algorithm (default settings). Duplicate reads were removed, and only uniquely mapped reads (mapping quality R 25) were used for further analysis. Alignments were extended in silico at their 30 ends to a length of 200 bp (the average genomic fragment length in the size-selected library) and assigned to 32-nt bins along the genome. The resulting histograms (genomic ‘‘signal maps’’) were stored in bigWig files. Peak locations were determined with the MACS algorithm (v2.1.0) with a cutoff P value = 10-7. Peaks that were on the ENCODE blacklist of known false ChIP-seq peaks were removed. Signal maps and peak locations were used as input data to the Active Motifs proprietary analysis program, which creates Excel tables containing detailed information on sample comparison, peak metrics, peak locations, and gene annotations.