SNX14 gene that lead to loss of protein function. Typically, these variants result in the formation of a premature stop codon, a shift in the reading frame or a variant in canonical splicing sites, as well as gross rearrangements. Here we present the first case of a deep intronic variant c.462-589A>G in SNX14 identified in two sisters with SCAR20 from a consanguineous family. This variant resulted in the inclusion of a pseudo-exon 82 nucleotides long and the formation of a premature stop codon, leading to the production of a truncated protein . Following an extensive diagnostic search, the diagnosis was confirmed using trio whole genome sequencing. This case contributes to expanding the spectrum of potential genetic variants associated with SCAR20.Autosomal recessive spinocerebellar ataxia type 20, SCAR20 (MIM: 616354) is a rare syndromic form of hereditary ataxias. It characterized by the presence of progressive ataxia, intellectual developmental disorder, autism and dysmorphic features. The disease caused by biallelic variants in  SNX14 lead to Autosomal Recessive Spinocerebellar Ataxia 20. This is the ultra-rare disease, with only 28 pathogenic and likely pathogenic variants described in the ClinVar database, in more than 36 patients from 19 families. Most of known causative variants assume the loss of protein functions (LoF) (The hereditary progressive ataxias comprise genetic disorders that affect the cerebellum and its connections . Autosomns (LoF) . Typicalns (LoF) .Often the diagnosis of SCAR could be challenging due to the high genetic heterogeneity with phenotypic similarity . To addrIn complex cases, the most effective is whole genome sequencing (WGS), as it allows to identify not only exon variants, but also variants located in introns, which can be regulatory or affect splicing . IntroniSNX14 gene, 589 base pairs away from the exon-intron junction. We demonstrated the molecular pathogenic mechanism underlying the formation of a novel donor splicing site within intron 5, resulting in the inclusion of a pseudo exon in RNA, leading to a frameshift.In this report, we describe a consanguineous family with two affected sisters, who have a homozygous variant located deep within an intronic region of the A family with two affected children  was examPatient V:1 is the first female child. Her mother experienced both toxicosis and anemia during the second pregnancy. At birth, she weighed 3,750 g, measured 52 cm in length, and received a good Apgar score of 8/8. However, she had neonatal jaundice for up to 2 months and was hypotonic. As she developed, she experienced delays such as holding her head up at 2 months, sitting at 11 months, walking with ataxia at 1 year and 7 months, and saying her first words at 2 years old. She is currently 13 years old, and while her growth and weight parameters have been normal, her occipitofrontal circumference (OFC) has measured 56 cm (+1.88 SD), which is above average.In addition, she has hypertelorism, epicanthus, dynamic ataxia, wide terminal phalanges of the thumbs and toes. She is able to speak a few words and eat with a spoon, but is not able to dress herself or perform self-care tasks. In terms of neurological status, patient exhibits spontaneous nystagmus, high pharyngeal and palatine reflexes, muscle hypertrophy of the limbs, reduced tendon reflexes, and no elicited knee and Achilles reflexes. Babinski’s reflex is present on both sides. MRI revealed cerebellar atrophy and periventricular leukopathy .Patient V:2 is a 7-year-old female who exhibits clinical features similar to her older sister. She was born during the third pregnancy, which was also complicated by toxicosis and anemia. At birth, she weighed 3,260 g, measured 52 cm in length, and received a good Apgar score of 9/9. However, within the first 2 weeks of life, her bilirubin levels increased to 205 μg/L.Since birth, Patient V:2 has experienced decreased reflexes, and her psychomotor development has been significantly delayed. She held her head up at 3 months, sat at 10 months, and walked unsteadily at 1 year and 2 months. Physical examination has revealed hypertelorism, epicanthus, high palate, wide umbilical ring, transverse palmar crease, and dynamic ataxia. In the neurological status, she has high tendon reflexes, and Babinski’s reflex is present on both sides. Nerve conduction study (NCS) results showed normal nerve conduction and amplitudes muscle responses.CACNA1A, ATXN1, ATXN2, ATXN3, ATXN7, ATXN8, PPP2R2B, FXN, and ATN1, which yielded negative results. Her karyotype was determined to be 46,XX. Furthermore, no variants were identified in her mitochondrial genome, WES, or chromosomal microarray (CMA) analyses.Patient V:1 underwent testing for short tandem repeats in several genes, including Trio whole genome sequencing (trio WGS) was performed in the case V:1. DNA was extracted from blood using a QIAamp DNA Blood Mini Kit (Qiagen). DNA purity was assessed by measuring DNA absorbance with NanoDrop (Thermo Fisher Scientific) at both 260/280 nm and 230/260 nm. DNA concentration was measured by Qubit fluorometer (Thermo Fisher Scientific) and a total of 2 µL of DNA, regardless of concentration, was then electrophoresed on an high-resolution capillary electrophoresis to determine the level of DNA fragmentation. Library preparation (PCR-Free) using MGI platforms then proceeded as protocols. Paired-end sequencing (2 х 150) was performed on the DNBSEQ-T7 (MGI). The data processing was carried out using “NGSData-Genome” program (Beskorovainy N.S. Program “NGSData”//Certificate of NGSData-Genome”//Certificate of State Registration of Computer Programs No. 2021662119.2021.) The reads were aligned to the reference genome hg19 using bwa v.0.7.17-r1188. Variants calling was performed with strelka2 v.2.9.10 and gatk v.4 algorithms. Colling of copy number variations–cnvkit 0.9.9; structural variants–manta v.1.6.0; tandem repeats–ExpansionHunterDenovo 0.9. Variant annotation–SnpEff v5.0, annovar v.2017, vep v.104.3. Splice predictors–dbNSFP v.4, SPiP v.2.1, mmsplice v.2.3, spliceai v.1.3.1, spidex v.1.The identified variants were confirmed by Sanger sequencing for the parents and affected sisters, using the ABI PRISM Big Dye Terminator (v 3.1) Cycle Sequencing Kit  on the ABI3130xl Genetic Analyzer .SNX14 (NM_153816.6) exons 3 to 7 was amplified using primers SNX14-ex3F (5’-TCATAGCTGTGCTGTTTGTGG-3’) and SNX14-ex7R (5’-TGCTTCATTGCTGCTTTTAAT-3’). PCR products were separated on a 2% agarose gel. Each DNA band was gel purified using Cleanup Standard kit  and further sequenced as described above.Total RNA from peripheral blood mononuclear cells (PBMCs) of one affected individual, both parents and three unrelated healthy controls were extracted using ExtractRNA reagent  according to the manufacturer’s recommendations. RNA samples were treated with DNAseI  and reverse transcribed using 5X RT MasMIX −30100 . A region harboring SNX14 (ClinVar: SCV003852744) was identified  and activated a cryptic acceptor splice site 82 bp downstream of the variant. Together, these can lead to the inclusion of a pseudo-exon into the SNX14 mRNA  in the phoresis  is not ephoresis , and minphoresis . Howeverphoresis . PerhapsSNX14 mutational spectrum with deep-intronic variant. Describing two patients from consanguine family with SCAR20. In our case WGS analysis was only possible diagnostic test that could reveal cause of disease. Due to genetic heterogeneity of ataxias the WGS has a significant advantage over WES for diagnostic.In this study we broaden the


An inflammatory response, related to colorectal cancer (CRC) progression, is a major subsequent result of bacterial infection following CRC surgery and should be of serious concern. Lipopolysaccharide (LPS), from the bacterial membrane, is a vital mediator of this event through binding with a Toll-like receptor 4 (TLR4) and activating through NF-κB in CRC. To identify a novel inhibitor of LPS-induced colon cancer cells (SW480), green coffee bean extract (GBE) was investigated. Ethyl acetate insoluble fraction (EIF) was mainly collected from GBE and classified as chlorogenic acid (CGA)-rich fractions. EIF and CGA inhibited TLR4 expression in LPS-induced SW480 cells. However, EIF was more dominant than CGA, via inhibition of expression and secretion of several associated mediators in inflammatory responses and CRC metastasis through NF-κB inactivation, which resulted in the abrogation of CRC migration and invasion. Thus, CGA-rich fraction from GBE can be further developed as an alternative treatment, coupled with CRC surgical treatment, to increase therapeutic efficiency and survival rate. In its early stages, colorectal cancer (CRC) is often cured following operative treatment. However, survival rates, following CRC resection, can be compromised, often as a result of bacterial infection during or post operation ,2; thereNormally, LPS acts on its specific receptor, named Toll-like receptor 4 or TLR4, located on the cell membrane of several cell types, especially in cancer cells. TLR4 is predominantly found in both inflamed intestinal and CRC cells ,8, whichIn some previous reports, anti-inflammatory drugs such as aspirin and celecoxib, delayed the progression of CRC ,19, but Coffee beans have two main strains, Arabica and Robusta. Two major compounds are well-known and plentiful in coffee beans, being caffeine (CF) and chlorogenic acid (CGA), especially in green coffee beans of the Robusta strain . Anti-GrCoffea canephora or Coffea robusta) were purchased from Doi Pha Hee, Chiang Rai province. They were crushed to a fine powder. Fifty grams of powder were shaken with 1 L of 60% methanol (in a ratio of 1:20 (w/v)) at room temperature. The filtrate was collected by Whatman No.1 and then concentrated to a final volume of 100 mL by the evaporator, called crude methanol extract (CME). Thereafter, CME (100 mL) was further separated with hexane to remove lipophilic fraction (in ratio 1:1) into 2 parts; hexane soluble fraction (HSF) and hexane insoluble fraction (HIF). HIF was further separated with ethyl acetate to decaffeinate (in ratio 1:1) into 2 parts; ethyl acetate soluble fraction (ESF) and ethyl acetate insoluble fraction (EIF). Following this, all of the fractions  were evaporated and lyophilized. Each fraction had its yield calculated as % yield and further chemical composition analysis was performed.Dried green coffee beans (2CO3), respectively. Each mixture was incubated at 45 °C for 15 min and then its absorbance was measured at 765 nm using a spectrophotometer. A standard curve of gallic acid was created and used to calculate the phenolic content of each fraction at 1 mg/mL. The results are shown as mg of the gallic acid equivalent (GAE) per 1 g of the dry weight sample.Total phenolic content was examined in accordance with Folin–Ciocalteu method . In shor2), distilled water, 10% aluminium chloride (AlCl3·6H2O) and 1M sodium hydroxide (NaOH), respectively. After 5 min, each sample was measured with a spectrophotometer; absorbance at 532 nm. Finally, a standard curve of catechin was formed and total flavonoid content of each fraction at 1 mg/mL was computed. These results are recorded as mg of catechin equivalents (CAE) per 1 g of the dry weight sample.A colorimetric assay with aluminum chloride was utilized for quantifying total flavonoid content . In brieTwo different methods were used for quantifying CGA, as well as CF, along with other phenolic acids, in all the fractions from GBE. For CGA detection, each fraction was separated on column ultra C18, 5 µM, 250 × 4.6 mm  using 0.2% phosphoric acid in water and acetonitrile as the mobile phase. A UV detector (DAD) was set at 330 nm. For CF and other phenolic acids detection, column platinum EPS C18 100A, 3 µM, 53 × 7 mm  and mobile phase 0.05% trifluoroacetic acid in 13% acetonitrile were used with the UV detector at 210 nm. Both methods were set at a flow rate of 1 mL/min. The results were displayed as HPLC chromatograms and identified by comparison with retention times (RT) of standard CGA, CF, and other phenolic acids . In the final analysis, the content of CGA, CF, and other phenolic acids were computed by using the standard curve of each standard  and shown as mg/100 g extract.50).The scavenging ability of each fraction to 2, 2-diphenyl-1-picrylhydrazyl or DPPH  was initiated with varying concentrations of each fraction (25–100 µg/mL). Each sample was incubated with 2 mM DPPH at room temperature for 30 min in darkness. The absorbance was detected at 517 nm and computed as the percentage of scavenging of DPPH by comparison with a blank control (100% DPPH or 0% scavenging ability). The blank was methanol instead of a sample. The results were expressed as a concentration of the sample at 50% scavenging of DPPH (SC50) was reported.The chelating of iron was also referred to anti-oxidant activity. Briefly, the different concentrations (100–500 µg/mL) of each fraction were set. Each concentration was incubated with 2 mM ammonium iron (II) sulfate solution and 5 mM ferene. After 10 min at room temperature, the color reaction was measured at 593 nm and calculated as the percentage of iron chelation (vs. blank control). The blank was methanol instead of a sample (100% iron or 0% iron chelation). A concentration of the sample at 50% iron chelation (EC2 within an incubator). Normal human dermal fibroblast cells (NHDF)  were used as the normal cell control and their growth condition was identical to the SW480 cells. SW480 cells were thoroughly pretreated with 1 µg/mL of LPS (in serum-free media) derived from Escherichia coli O26:B6  for 4 h.Human colon adenocarcinoma cell lines or SW480 cells  were chosen for the in vitro model. They were cultured in 10% fetal bovine serum (FBS) contained in Dulbecco’s Modified Eagle Medium (DMEM)  under proper conditions (37 °C and 5% CO3 cells/well in 96-well plate) were incubated at 37 °C for 24 h before being pretreated with LPS (1µg/mL for 4 h). The supernatant was removed and substituted with various treated conditions. After 24 h at 37 °C, cell viability or toxicity was detected by 3--2,5-diphenyltetrazolium bromide or MTT assay . MTT solution (5 mg/mL) also supplanted the prior condition media and was further placed in 37 °C for 2 h. The color was developed by adding dimethyl sulfoxide (DMSO). The absorbance was quantified at 540 nm, which allowed computation as the percentage of cell viability (vs. LPS control). Correspondingly, for verifying the toxicity to normal cells (NHDF), these were kept under identical conditions as the SW480 cells (under without LPS condition).SW480 cells . The sample was conditioned media from each treated (EIF or CGA) condition on LPS-pretreated SW480 cells for 24 h. All samples were processed by following the package insert, and the absorbance was measured at 450 nm and computed by comparison with a specific standard curve (pg/mL), as well as the total protein content (mg). Each secretory protein content  was finally shown as the percentage of the secretory protein content (vs. LPS control)® Laboratories, Hercules, CA, USA). The bands were visualized and captured using a chemiluminescence detector . Finally, the intensity of each band was analyzed and normalized with its β-actin band.An immunoblotting assay was used for analyzing the expression level of several associated mediators of LPS-TLR4 signaling; these included TLR4, TNF-α, IL-1β, COX-2, VEGFC, pp65, and p65. In short, the cell lysate, from various treated conditions on LPS-pretreated SW480 cells (at 37 °C for 24 h), was equally loaded onto 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Thereafter, gels were blotted onto polyvinylidene difluoride (PVDF) membranes, which were continuously blocked by 5% skimmed milk powder in PBS-T (0.05% Tween-20 in PBS). Afterward, membranes were incubated with diluted specific primary antibodies against TLR4, TNF-α, IL-1β, COX-2, pp65, p65, VEGFC, and β-actin  at 4 °C overnight. For detection, membranes were soaked with diluted HRP-conjugated secondary antibody  at room temperature and further reacted with the enhanced chemiluminescence (ECL) substrate (Bio-Rad4 cells/mL in 1% BSA in serum-free medium) were suspended with each concentration of EIF or CGA in a ratio of 1:1 at room temperature. Then, each mixture (100 µL) was added into 50 µg/mL of Matrigel  coated 96-well plates (in triplicate), and then placed at room temperature for 1 h. Non-adherent cells were removed and replaced with MTT solution for measuring the remaining cell-Matrigel adhesion. The absorbance was detected and calculated as a percentage of cell adhesion ability.LPS-pretreated SW480 cells (at 50 × 106 cells/well) were seeded into 6-well plates at 37 °C for 24 h and then the media was removed. Each conditioned media was added and then the gap (at 0 h) was created by the pipette tip. The migratory distance was measured after incubation at 37 °C for 24 h, by using an inverted microscope (10×) and Zen imaging software. The picture of each condition (at 0 and 24 h) and its percentage of cell migration (vs. LPS control) was computed and presented.This method is commonly used to verify the effect of compounds on cell migration by measuring the distance of cell travel (2D movement). To start, LPS-pretreated SW480 cells (at 2 × 106 cells/mL in serum-free media (0% FBS in DMEM), and each concentration of EIF or CGA (in ratio 1:1), was placed on the upper part of the Transwell® with an 8 µM-pore-polycarbonate membrane (in duplicate). The lower part of the chamber contained 600 µL of 10% FBS in DMEM. The cell motion at the lower part of the membrane was detected after incubation at 37 °C for 24 h by staining and fixing with 1% crystal violet in 50% methanol. Non-motion cells were removed with a cotton swab. Each membrane was cut and dissolved with 20% acetic acid. The absorbance was measured at 570 nm, which directly correlated with cell migratory ability. The data was expressed as a percentage of cell migration by comparison with LPS control (100% cell migration).This migration is dependent on the concentration gradient of the chemoattractant (3D movement). Firstly, 100 µL of the mixture of LPS-pretreated SW480 cells at 2 × 106 cells/mL) and each treated condition (in a ratio of 1:1) in serum-free media was placed into the upper chamber (in duplicate). In the lower part, 10% FBS in DMEM was also added. After 24 h, the cell invasion was detected by staining and fixing with 1% crystal violet in 50% methanol. Non-invasive cells were cleared with a cotton swab. The absorbance of each membrane in 20% acetic acid was measured at 570 nm. The percentage of cell invasion (vs. LPS control) was displayed.The cell invasion assay, or Transwell migration assay, was performed by coating Matrigel (basement membrane matrix) on the membrane. Similarly, the mixture of LPS-pretreated SW480 cells  via the SPSS program. The major symbols were determined as significant values (vs. LPS control), including 50), while EIF was more efficient in iron chelation (less EC50)  .20) range of each substance, including 25–75 µg/mL of EIF and ESF, 5–20 µg/mL of CGA and 20–60 µg/mL of CF. Of note, these concentrations of each substance were also shown to be nontoxic to the cell viability of normal fibroblast cells or NHDF   G–I.TLR4 is the primary target of LPS stimulation. LPS acts as an inducer of TLR4 expression on SW480 cells (approximately 15–20% of induction in this study). We found interesting results regarding substances that could affect this LPS-TLR4 pathway. Not only did EIF treatment dominantly downregulate TLR4 expression on LPS-induced SW480 cells in a dose-dependent pattern, especially at 50 and 75 µg/mL A,B, but Increased levels of inflammatory mediator expression and secretion are the result of the action of the LPS-TLR4 trigger. TNF-α, IL-1β, IL-6, and COX-2 expression and secretion were increased in LPS-activated cells. These LPS actions were clearly disrupted, not only expression  A–D but aVEGFC is one of the main secretory proteins associated with various steps of colon cancer progression. Here, the cancer-inducing property of LPS has been demonstrated by the increase of VEGFC expression (18%) and secretion (40%) from SW480 cells, whereas its inductions were inhibited after adding EIF or CGA in a dose-dependent action A–C.w/wo chemoattractant condition was significantly abrogated by EIF treatments, especially at 75 µg/mL. Meanwhile, anti-migration of CGA was selectively found, without a chemoattractant condition (2D movement) in a dose-dependent pattern , while the other treated conditions showed no significant differences in the ratio of pp65/p65 (vs. LPS control), which is definitely related to their actions on pp65 and p65 levels  to upregulation of p65 levels in SW480 cells, compared with no LPS condition; this is similar to our previous study [5 levels D.Even though the adverse effects of infection with pathogenic bacteria during CRC surgery are well known, there is still limited investigation, other than antibiotic therapy, related to other agents to minimize these serious events. Our previous publication was first able to identify the inhibitory role of a gamma oryzanol-rich fraction from purple rice on LPS-induced inflammatory responses and CRC progression, via pathways of TLR4 and NF-κB ,27,28. HBecause TLR4 is the primary target of LPS and highly expressed in CRC, our results explored that LPS-induced TLR4 expression in SW480 cells was obviously suppressed by EIF and CGA treatment, but not ESF and CF. Thus, EIF and CGA were more interesting than ESF and CF; both need further studying regarding LPS-TLR4 sequelae. In this step, the inhibitory effect of EIF seemed to be stronger than CGA, because the effective dose of CGA was only performed at 20 µg/mL with less effect than EIF at 75 µg/mL (containing CGA 13.3 µg/mL).Next, inflammatory responses are common subsequences of LPS-TLR4; the increased expression and secretion of several inflammatory mediators are found ,20,31. SDuring CRC progression, LPS was reported as a potent inducer of CRC metastasis via VEGFC modulation , so the Finally, to clarify an associated regulatory pathway, NF-κB is the major downstream regulator of the LPS-TLR4 signaling pathway and also connects with VEGFC expression. Our previous study found that LPS, preferably activated via phosphorylation of p65, but not p65 levels in CRC ,31, corrIn conclusion, this study encourages the potential utilization of EIF or CGA-rich fraction from GBE as part of a novel, additive CRC treatment. Although, CGA is a major component and participated in some inhibitory events, it was not dominant. The synergistic effect of the mixture of compounds in EIF was highlighted, as were their impact on LPS responsiveness of CRC, namely inflammatory response, and CRC progression. Thus, it should be considered and further developed to be a safe and efficient adjunct coupled with current CRC resection in the future.


Valeriana pilosa are commonly used in Peruvian folk medicine for treating gastrointestinal disorders. This study aimed to investigate the spasmolytic and antispasmodic effects of Valeriana pilosa essential oil (VPEO) on rat ileum. The basal tone of ileal sections decreased in response to accumulative concentrations of VPEO. Moreover, ileal sections precontracted with acetylcholine (ACh), potassium chloride (KCl), or barium chloride (BaCl2) were relaxed in response to VPEO by a mechanism that depended on atropine, hyoscine butylbromide, solifenacin, and verapamil, but not glibenclamide. The results showed that VPEO produced a relaxant effect by inhibiting muscarinic receptors and blocking calcium channels, with no apparent effect on the opening of potassium channels. In addition, molecular docking was employed to evaluate VPEO constituents that could inhibit intestinal contractile activity. The study showed that α-cubebene, β-patchoulene, β-bourbonene, β-caryophyllene, α-guaiene, γ-muurolene, valencene, eremophyllene, and δ-cadinene displayed the highest docking scores on muscarinic acetylcholine receptors and voltage-gated calcium channels, which may antagonize M2 and/or M3 muscarinic acetylcholine receptors and block voltage-gated calcium channels. In summary, VPEO has both spasmolytic and antispasmodic effects. It may block muscarinic receptors and calcium channels, thus providing a scientific basis for its traditional use for gastrointestinal disorders.Infusions of  Gastrointestinal disorders are related to motility disturbances, visceral hypersensitivity, altered mucosal and immune functions, gut microbiota dysbiosis, and impaired regulation by the central nervous system . GastroiMedicinal plants are complex mixtures of compounds that have served as sources of drugs for centuries. Approximately half of the current pharmaceutical therapies are derived from medicinal plants .Little is known about the effects of essential oils on the intestinal microbiota , which hValeriana pilosa R & P. is a plant belonging to the genus Valeriana and distributed in the Andean region. In Peru, it is known as “Valeriana”, “Coche coche”, ‘‘Valeriana de paramo’’, ‘‘Ornamo’’, or “Babilla”. Vertical rhizome and attached roots from Valeriana pilosa are widely used as antispasmodic, relaxing, anti-inflammatory, and sleep-promoting agent [ng agent ,13.Our continuous interest in the volatile components of plant species from Chilean and Peruvian Andean highland communities has been the focus of our chemical and biological research projects ,17,18,192 muscarinic acetylcholine receptors (M2R), M3 muscarinic acetylcholine receptors (M3R), and voltage-gated calcium channels (Cav1.2).In this study, we report spasmolytic and antispasmodic activities of VPEO on intestinal contractile activity. The VPEO-mediated effect appears to be mediated by muscarinic receptor antagonism, calcium channel blockade, and potassium channel opening, which may explain the traditional use of the plant in gastrointestinal disorders. Additionally, we performed in silico molecular docking analyses of the major constituents in VPEO and found that some molecules have the potential to bind to M2), ethylenediaminetetraacetic acid (EDTA), calcium chloride (CaCl2), glibenclamide, D-glucose, magnesium chloride (MgCl2), potassium chloride (KCl), potassium dihydrogen phosphate (KH2PO4), sodium bicarbonate (NaHCO3), sodium chloride (NaCl), sodium phosphate monobasic (NaH2PO4), and verapamil were purchased from Sigma-Aldrich  and Merck .Acetylcholine hydrochloride (ACh), barium chloride  of All chemicals were of analytical reagent grade; they were obtained from Sigma-Aldrich-Fluka  and Merck , and were used as supplied. Chromatographic analysis of VPEO was performed using a Perkin Elmer Clarus 600 gas chromatograph, following to the procedure reported by Benites et al. .9–C21 n-alkane indices and GC–MS spectra from the mass spectra library and commercial sample standards.GC–MS analysis of VPEO was carried out as previously reported . BrieflyRattus norvegicus Holtzman, 170–200 g) were housed in cages  with ad libitum access to standard rat chow  and water.The experiments in this study were performed following the procedures of the American Veterinary Medical Association (AVMA)  and the 2 1.8; MgCl2 1.05; NaHCO3 11.9; NaH2PO4 0.42; and D-glucose 5.55 [2 and 5% CO2 (pH 7.4). Resting tension was fixed at 1 g. The experimental data were recorded using a Power Lab 26T system  with the LabChart 8 program for Windows .Animals were sacrificed by cervical dislocation. A portion of the ileum (2.5 cm), without considering the 10 cm nearest to the ileocecal valve, was removed and placed into a petri dish containing Tyrode’s solution (concentrations in mM): NaCl 136.9; KCl 2.68; CaClose 5.55 . Ileum fThe contractility of the rat ileum in response to VPEO was assessed through cumulative dose–response experiments. A series of seven distinct concentrations of VPEO  were administered in 5 min intervals .2)-containing solutions [−5 M), KCl (60 mM), or BaCl2 (5 mM) for 10 min or until a stable contractile plateau (plateau) was reached. Then, different VPEO concentrations  were sequentially added to the tissue chamber.Neurotropic spasm was induced using acetylcholine (ACh), whereas musculotropic spasm was induced using highly concentrated potassium chloride (KCl)- or barium chloride (BaClolutions . Isolate−10 to 10−3 M) before and after VPEO (250 and 500 μg/mL) administration were performed in the same experiment.The effect of VPEO on the contractibility in response to ACh was assessed as follows: dose–response experiments  or BaCl2 (10−8 to 10−2 M) were performed.Similar experiments to those described above but contracting the ileal sections with KCl . Then, the tissue was washed with normal Tyrode’s solution for at least 10 min, followed by the addition of VPEO (250 and 500 μg/mL) for 20 min [In addition to the Tyrode´s solution, a calcium-free solution was prepared for this experiment. The solution had the following composition (concentrations in mM): KCl 50; NaCl 91.04; MgClEDTA 0.1 . Initialr 20 min .−5 M, followed by increasing CaCl2 concentrations .After VPEO incubation in normal Tyrode’s solution, intestinal sections were incubated with VPEO-supplemented calcium-free solution, then contracted with ACh 10The tension was re-adjusted in the middle of the experiment to 1 g when necessary .2–M3 blockers) [3 blocker) [To analyze the role of VPEO in muscarinic receptor activity, experiments were carried out in the absence/presence of atropine (a non-selective muscarinic antagonist) , hyoscinlockers) , or soliblocker) . First, To determine whether the effect of VPEO was related to the inhibition of voltage-gated calcium channel, experiments were performed in the absence and presence of verapamil . Initially, the tissue was stabilized for 1 h and then washed in 15 min intervals (4–5 times). The tension was adjusted again to 1 g if necessary. The tissue was pre-incubated with verapamil (1.0 μM)  for 20 m+ channel blockers, namely, glibenclamide [The role of K⁺ channels in VPEO-induced relaxation was investigated by pre-incubating the ileum rat for 20 min with two Knclamide  , 4DAJ (M3 Muscarinic Acetylcholine Receptor), and 5V2P . Data was obtained from the Protein Data Bank [3. The center of the binding site were the following coordinates for each of the proteins studied  was selected for evaluation. Docking results in 3D representations were obtained using Discovery Studio [All other parameters were set to their default values as defined by AutoDock Vina. Dockings were repeated 10 times, with the space search exhaustiveness set to 100. The best interaction binding energy , Binding Efficiency Index (BEI), Lipophilic Ligand Efficiency (LLE), and Non-Covalent Interaction Index (NCI) were calculated according to a previously reported procedure [Ligand Efficiency  was used for the statistical analyses. Non-linear regression analysis (three-parameter Hill function) was generated to compare dose–response curves. Two-way ANOVA analysis followed by the Bonferroni post hoc test was used to evaluate the significance between different groups.p < 0.01) (p < 0.05).VPEO significantly decreased the muscle tone of the rat ileum at 100 µg/mL  A. VPEO-m−5 M ACh (muscarinic agonist) (2+ channels)   10agonist) B, (b) 60hannels) C, and  D.2. For instance, 100 µg/mL VPEO relaxed ileal sections precontracted with ACh, KCl, and BaCl2 by 54.62 ± 5.7%, 60.88 ± 6.2%, and 73.89 ± 2.2%, respectively.VPEO significantly relaxed, in a dose-dependent manner, precontracted intestinal segments with ACh, KCl, and BaClp < 0.05) the ACh-induced contraction (10−7 M ACh): 40.5 ± 8.45% (control) vs. 18.4 ± 1.96% (VPEO); −7 M) was suppressed , as shown in 50 values for ACh in the presence of 250 µg/mL (6.22 ± 0.09) and 500 µg/mL (5.75 ± 0.08) of VPEO were significantly different to that obtained under control conditions (6.53 ± 0.11).Experiments were performed to determine whether VPEO modifies ACh-evoked intestinal contractions in the intact rat ileal tissue. Initially, ileum contractions were recorded before and after VPEO treatment A. VPEO a−2 M KCl: 71.46 ± 8.93% (p < 0.05) and 38.58 ± 9.74% (p < 0.001) compared to the control in the presence of 250 µg/mL and 500 µg/mL VPEO, respectively . Similar results were observed for 10−1.5 M KCl: 62.82 ± 6.03% (p < 0.01) and 59.03 ± 10.46% (p < 0.01) compared to the control in the presence of 250 µg/mL and 500 µg/mL VPEO, respectively (50) in the presence of 250 µg/mL (2.12 ± 0.25) and 500 µg/mL (1.74 ± 0.29) VPEO was not significantly different from that obtained under control condition (2.19 ± 0.22).ectively B.1. Simiectively B.1. Simi2 (10−8–10−2 M) block not only inward rectifier potassium channels (KIR), but also voltage-gated potassium channels (VGKCs). In 2 in the presence and absence of VPEO are recorded. Pre-incubation with VPEO significantly reduced the contraction induced by 10−4 M BaCl2: 23.75 ± 2.47%  and 31.18 ± 11%  and 73 ± 5.2%  in the presence of 250 µg/mL (3.35 ± 0.06) and 500 µg/mL (3.68 ± 0.18) VPEO was not significantly different from that obtained under control condition (3.95 ± 0.36).On the other hand, high concentrations of BaCl2–M3 muscarinic antagonist), and solifenacin (M3 selective muscarinic antagonist), at doses of 1 μM; then, concentrations of VPEO were added.After observing that VPEO reduced the effect of ileum contractions induced by ACh, we studied how VPEO affected the blockade of muscarinic receptors. The intestinal strips were pre-incubated with atropine (a non-selective muscarinic antagonist), hyoscine butylbromide (Mp < 0.05) reduced (0.67 ± 5.54% and 0.63 ± 10.55%) compared to ileal tissues that were not pre-incubated with antagonists (29.37 ± 4.82%). At the highest dose of VPEO (1000 μg/mL), the relaxation was more significant against atropine 1 μM  than in hyoscine butylbromide 1 μM  compared to the control (57.15 ± 5.84%). On the other hand, the relaxant dose–response of VPEO in the presence of solifenacin 1 μM decreased compared with that of the control, albeit not significantly (p > 0.05), as shown in 3 and M2 receptors mediate the relaxant effect of VPEO.These results indicate that the blockade of M2+ ions (0 to 1 mM) in ileum rats precontracted with ACh (10−5 M) maintained in Ca2+-free Tyrode’s solution (containing 0.1 mM EDTA) in the presence and absence of VPEO was determined  significantly decreased the contraction induced by CaCl2 0.6 mM. However, the concentration–response curve produced by the different concentrations of calcium ions was significantly decreased in the presence of VPEO compared to the control (The relation between the relaxant effect of VPEO (250 and 500 μg/mL) and extracellular calcium was assessed. The contraction induced by the cumulative concentration of extracellular Catermined A. The cu control B.p < 0.05, The relaxant effect produced by VPEO was decreased in the presence of verapamil 1 μM  and barium chloride  was studied. The relaxation induced by VPEO in the rat ileum was unaffected by glibenclamide A or BaCl2 B treatmeValeriana pilosa roots (VPEO). A total of 47 compounds were identified, where sesquiterpene hydrocarbons, monoterpene hydrocarbons, oxygenated monoterpenes, and oxygenated sesquiterpenes were the major constituents. Within the sesquiterpenes, the major constituents of VPEO were α-patchoulene (5.8%), α-humulene (6.1%), seychellene (7.6%), and patchoulol (20.8%), as well as spathulenol, T-cadinol, and γ-cadinol as minor constituents [We have recently described the chemical composition and antioxidant activity of the essential oil from tchoulol .8%, as w2 and M3 Muscarinic Acetylcholine Receptor and Cav1.2 . 2 and M3 muscarinic acetylcholine receptors.Molecular docking was performed to identify possible VPEO constituents that could inhibit some proteins involved in intestinal contractile activity. Based on the results obtained in the current study, we selected M2 and M3 muscarinic acetylcholine receptors appeared to be the best protein targets for some VPEO constituents, as shown by their intermolecular docking energy (∆bindingE), score normalization of the binding energy based on the number of non-hydrogen atoms (norm.bindingIE), and Ligand Efficiency (LE) values. Indeed, using the weighted arithmetic mean values  protein target, the ∆bindingE, LE, and norm.bindingIE, binding values were −5.11, 0.37, and −1.37 kcal·mol−1. Therefore, these results show that the M3 muscarinic acetylcholine receptor, as a target protein, is probably involved in the effects of VPEO, which means that they might be involved in the anti-spasmodic activities of VPEO compounds. Based on the information shown in d values, Ligand Efficiency (LE), Binding Efficiency Index (BEI), Lipophilic Ligand Efficiency (LLE), and normalization of the binding energy score based on the number of non-hydrogen atoms (norm.bindingIE) are summarized in 2 Muscarinic Acetylcholine Receptor) and 11 (M3 Muscarinic Acetylcholine Receptor) compounds, of which the most abundant compounds found in the VPEO are presented. The results showed that approximately 60% of the VPEO compounds acted as potential blockers of M2 and M3 Muscarinic Acetylcholine Receptors. In contrast, the others showed higher values and were considered weak blockers with low activity for the other protein target Cav1.2 .Molecular docking analyses, K2 Muscarinic Acetylcholine Receptor were β-patchoulene, β-caryophyllene, γ-muurolene, and eremophyllene, while for the M3 Muscarinic Receptor were α-cubebene, β-patchoulene, β-bourbonene, β-caryophyllene, α-guaiene, α-humulene, γ-muurolene, valencene, and δ-cadinene, all obtained ∆bindingE values (<−9.0) and norm, bindingIE values (<−2.2), representing those with the highest interaction with residues close to the active site. In addition, the binding energies were evaluated for the major VPEO compounds, including natural sesquiterpenes such as α-patchoulene (5.8%), α-humulene (6.1%), seychellene (7.6%), and patchoulol (20.8%). and the major VPEO compounds that interact with the Ming site . These i3-ligand complex. The five best compounds, such as α-cubebene, β-patchoulene, β-bourbonene, β-caryophyllene, α-guaiene, γ-muurolene, valencene, and δ-cadinene, found by molecular docking present weak Van der Waals-type and π–alkyl interactions with the aromatic binding site of M3, where the most representative residues are Tyr506, Tyr148, Phe239, Trp503, Tyr506, Trp199, and Tyr529. On the other hand, the major constituents of the VPEO as α-patchoulene, α-humulene, seychellene, and patchoulol, had similar interactions of weak Van der Waals-type and π–alkyl interactions with the aromatic binding site of M3, where the most representative residues of these interactions are Ala235, Cys532, Val155, Trp503, Tyr506, and Tyr529. However, patchoulol has a hydrogen bridge interaction between the hydroxyl group and Asn507, favoring the potential binding of this compound to M3.Valeriana pilosa root essential oil (VPEO) and its underlying mechanisms of action using the isolated rat ileum ex vivo model. Our findings reveal that VPEO displays spasmolytic and antispasmodic effects in a dose-dependent manner at concentrations ranging from 100 to 1000 μg/mL. The relaxant activity of VPEO in the isolated rat ileum was reversible after washing, indicating that the inhibition observed was not attributable to intestinal damage caused by the oil’s interaction with cell lipid bilayers [Essential oils are gaining interest due to their intricate chemical composition and diverse pharmacological effects. Among these actions, the antispasmodic effect is well known, although further research is required to better understand the cellular and molecular mechanisms of action . Therefobilayers .1–M5 [2 and M3 subtypes, with M2 being predominant (M2:M3 = 3–5:1) [Smooth muscle excitation and contraction in response to acetylcholine (ACh) release from autonomic nerves primarily involve the activation of muscarinic acetylcholine receptors (mAChRs) in the gastrointestinal tract and many other visceral organs . The mAC1–M5 . Smooth = 3–5:1) ,45, alth= 3–5:1) .50 of the tissue to ACh, as evidenced by a rightward shift in the dose–response curve. These initial findings suggest that VPEO blocks muscarinic receptors involved in rat ileum contraction. To explore this hypothesis, we evaluated whether the presence of muscarinic antagonists such as atropine, hyoscine butylbromide, and solifenacin would attenuate the relaxing effect of VPEO. Our results showed that solifenacin, a selective blocker of M3 muscarinic receptors, slightly reduced the relaxation induced by VPEO, but not significantly. In contrast, hyoscine butylbromide, an M2–M3 muscarinic blocker, significantly reduced the relaxing effect of VPEO. Moreover, when the non-selective muscarinic blocker atropine was employed, the relaxing effect of VPEO on muscle tone in the rat ileum was further reduced. Traditional studies using various mAChR antagonists have suggested that the M3 subtype primarily mediates contraction in visceral smooth muscles, while the contribution of the M2 subtype remains less clear [2 subtype modulates contraction, at least in part, by inhibiting cyclic AMP (cAMP)-dependent relaxation [3 receptors, the antispasmodic effect of VPEO also involves modulation of M2 receptors. Consequently, both experimental and theoretical outcomes reveal the impact of VPEO on M2 and M3 muscarinic receptors.Activation of mAChRs triggers multiple biochemical and electrical signaling events that result in muscle contraction . Our resss clear ,49. Howelaxation  and regulaxation ,52. NeveThere is limited research available on the effects of essential oils on cholinergic receptors expressed in smooth muscle, and a few studies have been published . MoleculHigh concentrations of potassium ions (hypermolar KCl) cause tonic contraction of smooth intestinal muscles by a mechanism that depends on extracellular calcium influx ,57. Our Valeriana hardwickii Wall, which caused a rightward shift in calcium concentration-response curves in the rabbit jejunum, similar to that caused by verapamil [Furthermore, it was confirmed that the relaxation induced by VPEO was reduced in the presence of verapamil, a voltage-gated calcium channel blocker. These results are consistent with similar studies conducted on the rhizome of erapamil ,61. The ATP) channels regulate intestinal contractility [+ channel (KIR) and subunits of the sulfonylurea regulatory receptor (SUR). The data demonstrate decreased intrinsic basal contractility in the small intestine and colon due to increased basal KATP channel activity, which can be inhibited by glibenclamide, an ATP-sensitive K⁺ channel blocker [2, an inward rectifier K⁺ channel blocker [2-induced contractions, shifting the dose–response curve to the right, suggesting that VPEO might activate K+ channels, similar to the crude extract of Valeriana wallichii, which displays antispasmodic activity mediated by activation of the KATP channel [2, and the relaxing effect of VPEO on basal tone was evaluated. Our results showed that the activation of KATP and KIR channels did not produce the relaxation exhibited by VPEO in the rat ileum.It has been shown that ATP-sensitive potassium  unequivocally demonstrated its spasmolytic and antispasmodic effects in rat ileum. In silico and pharmacological analyses suggest that VPEO exerts its actions through blockade of muscarinic receptors and calcium channels. Collectively, these outcomes provide molecular insights that shed light on the traditional utilization of this plant for the treatment of gastrointestinal disorders.The findings obtained from this study on


Ion mobility (IM) adds a new dimension to liquid chromatography-mass spectrometry-based untargeted metabolomics which significantly enhances coverage, sensitivity, and resolving power for analyzing the metabolome, particularly metabolite isomers. However, the high dimensionality of IM-resolved metabolomics data presents a great challenge to data processing, restricting its widespread applications. Here, we develop a mass spectrum-oriented bottom-up assembly algorithm for IM-resolved metabolomics that utilizes mass spectra to assemble four-dimensional peaks in a reverse order of multidimensional separation. We further develop the end-to-end computational framework Met4DX for peak detection, quantification and identification of metabolites in IM-resolved metabolomics. Benchmarking and validation of Met4DX demonstrates superior performance compared to existing tools with regard to coverage, sensitivity, peak fidelity and quantification precision. Importantly, Met4DX successfully detects and differentiates co-eluted metabolite isomers with small differences in the chromatographic and IM dimensions. Together, Met4DX advances metabolite discovery in biological organisms by deciphering the complex 4D metabolomics data. The high dimensionality of ion mobility (IM)-resolved metabolomics data presents a great challenge to data processing. Here, authors develop a mass spectrum-oriented bottom-up assembly algorithm and the end-to-end computational framework Met4DX for IM-resolved metabolomics. However, the enormous chemical and the compositional diversity of metabolome presents a grand challenge in separation and identification of metabolites. This challenge is particularly prominent for isomeric metabolites, which tend to co-elute on chromatography and share similar fragments in MS/MS spectra4. Recently, liquid chromatography–ion mobility–mass spectrometry (LC–IM–MS) has been emerging as a promising technology for four-dimensional untargeted metabolomics6. Ion mobility adds a new dimension of separation to LC–MS. After ionization, ion mobility separates metabolite ions according to their sizes, shapes, and charges in gas phase on the millisecond timescale, which effectively improves the resolving power and selectivity without adding to analysis times9. The ion mobility-derived collision cross-section (CCS) is a valuable physiochemical property for metabolite identification with high reproducibility across different instruments13. The hyphenation of IM with LC and tandem MS provides a promising strategy for the multidimensional analysis of the complex metabolome16. This technology has demonstrated distinct advantages over conventional LC–MS, including improved separation and peak capacity, capability to separate and differentiate metabolite isomers, and generation of four-dimensional (4D) data  for metabolite identification17.Mass spectrometry-based untargeted metabolomics has become increasingly successful in providing a comprehensive, unbiased and quantitative characterization of metabolites in a biological system under investigation21, very few software tools were developed for 4D metabolomics24. Mass spectra generated from ion mobility-resolved untargeted metabolomics are structurally complex because of the additional ion mobility dimension. For 4D peak detection in such complex dataset, the top-down based dimensionality reduction is often employed. For example, in 4D proteomics, software tools such as MaxQuant18 and IonQuant19 slice the 4D data space  into multiple 3D sub-spaces  along the ion mobility dimension  by summing the ion mobility dimension . For each bin, 3D distances between any of two MS2 spectra are calculated by integrating the similarities of ion mobility and RT of their precursor ions and MS2 spectra. Then, a hierarchical cluster analysis (HCA) is applied using the 3D distances among MS2 spectra in the bin, and generates the unique MS2 clusters for each bin. Finally, the MS2 spectrum with the highest spectral intensity (termed as unique MS2 spectrum) is selected to represent the cluster. The dereplication step significantly reduces the redundancy of MS2 spectra for subsequent peak detection.In data-dependent MS2 acquisition (DDA), for example, parallel accumulation serial fragmentation (PASEF)-DDA in trapped ion mobility mass spectrometer (TIMS)ion Fig. . Specifim/z-ion mobility data frame with the precursor m/z, ion mobility, and frame index recorded in the mgf file. In step 2, the adjacent MS1 data points from the same m/z-ion mobility frame are retrieved to assemble a possible ion mobility peak. Then, peak detection is performed in ion mobility dimension. If a successful extracted ion mobilogram (EIM) peak is obtained, in step 3, MS1 data retrieval and assembly of EIM peaks are repeatedly extended to the adjacent m/z-ion mobility frames . After that, in step 4, all MS1 data points from EIM peaks in each mobility frame are summed up to rebuild the ion chromatogram in LC dimension. Similarly, peak detection is also performed in the assembled ion chromatogram . If a successful EIC peak is obtained, in step 5, a 4D peak is constructed with recorded apex and boundary information in EIM and EIC detections. Peak intensity is generated from 3D peak volume. Most importantly, Met4DX employs a serial of criteria during 4D peak detection to reduce false positive and improve peak fidelity (see Methods). Collectively, peak detection in Met4DX starts from one MS2 spectrum and constructs the 4D peak in a reverse order of the sequential separation in LC–IM–MS. Therefore, we refer our peak detection as a bottom-up assembly strategy.Second, we developed a MS spectrum-oriented bottom-up assembly algorithm for 4D peak detection, which is the core module of Met4DX Fig. . The 4D m/z, retention time, mobility, and MS/MS spectrum). Matched peaks are employed as landmarks to construct a retention time regression model for retention time correction and peak alignment. A density-based peak grouping strategy is further applied with the distribution of m/z and ion mobility values. Peak match between samples is also performed to overcome the stochasticity during data acquisition. Finally, gap filling is applied for missing values through targeted extraction. A 4D peak table is generated for metabolite quantification in multiple samples and groups, while related 4D information for each feature  is also outputted. Fourth, metabolite annotation is performed through multidimensional match . In summary, Met4DX is a MS spectrum-oriented computational tool to provide an end-to-end data processing for 4D untargeted metabolomics. Met4DX is now freely available as an R package in GitHub.Third, 4D peak alignment and grouping is performed to combine multiple samples for quantification Fig. . Specifitch Fig. . In Met4We demonstrated 4D peak detection of Met4DX with NIST human urine samples  acquired using TIMS with PASEF-DDA technology. In positive mode, a total of ~25,000 MS2 spectra acquired from each sample were inputted into Met4DX for 3D binning and MS2 spectral dereplication Fig. . Most clm/z = 190.0500 Da; mobility,1/K0 = 0.640 V·s/cm2; frame index = 1056) was generated to initiate peak detection. Met4DX first searched and retrieved its precursor data point with m/z and mobility information in the frame 1506. Then, adjacent MS1 data points in the same frame were also retrieved to assemble the IM peak. The peak apex was determined at 1/K0 of 0.640 V·s/cm2. The same IM peak assembly was repeatedly implemented in adjacent frames  and validation by the chemical standard  to evaluate peak detection performance of Met4DX, including coverage, sensitivity, and peak fidelity. Other software tools such as MS-DIAL and MetaboScape  were used for comparison. Met4DX achieved a total of 6500–8700 and 4400–6800 features in positive and negative modes, respectively, for different sample types Fig. –3. The b26. A 4D peak with good EIC or EIM peak shape was recognized as a true 4D peak. We selected the replicate sample with the highest peak intensity for evaluating peak fidelity. For NIST human urine samples, we exported and manually checked 7287 EIC and 7287 EIM peaks in positive mode, and 6889 EIC and 6889 EIM peaks in negative mode, respectively. For NIST human urine samples, 97% and 93% of 4D peaks were manually checked with good peak fidelity in positive and negative modes, respectively  of peak intensities indicates that Met4DX had substantially higher quantification precision compared to MS-DIAL and MetaboScape Fig. , with mem/z, CCS, RT, and MS/MS spectra  have at least one isomer (with the same formula). A total of 1,648,4071 pairs of metabolite isomers were generated. We calculated RT and CCS values for all metabolites and found that LC could resolve 18% of isomer pairs . For isomeric pairs with 0.5% of ΔCCS, the separation can only be achieved when the IM resolving power reaches >25030. In this case, 92% of isomeric pairs could be resolved , generating a total of 14,528 IM co-eluting isobaric feature pairs. Among them, 12,690 pairs (87%) had ΔRT larger than 20 s  had MS2 spectra  achieved IM resolving power up to 500–1000. With these advancements, Met4DX will become more effective to discriminate isomeric metabolites in complex metabolome, which will empower the widespread applications of ion mobility-resolved 4D metabolomics.Isomeric metabolites commonly exist in metabolome and could not be fully resolved by conventional LC–MS. They tend to co-elute on chromatography, co-fragmentation and share similar fragments in MS/MS spectra, restricting the accurate metabolite identification in LC–MS-based untargeted metabolomicstes Fig. –19. Smaltes Fig. . Additio33 and MetDNA34), and in silico prediction tools  have readily facilitated metabolite annotation. With the development of Met4DX, it become feasible to expand more analytical dimensions to support multidimensional metabolite annotation including LC separation-derived RT and IM separation-derived CCS. The combination of LC and IM separations with MS measurements has been proved to improve resolving power, selectivity, and sensitivity, thereby benefiting the fidelity of metabolite annotation17. We demonstrated that Met4DX is particularly prominent to achieve high-coverage 4D peak detection with 4D information  of metabolites, maximizing information coverage to support in-depth metabolite annotation. We believe the integration of Met4DX with state-of-art metabolite annotation strategies, such as network-based tools  and in silico prediction tools  will further increase the coverage and accuracy of metabolite annotation in metabolomics. For 4D metabolomics, in the past decade, many CCS prediction tools38 with high accuracy were developed (with CCS prediction errors of 1–2%). However, the CCS prediction accuracy highly depended on the coverage of training datasets and training models. For some compounds lacking similar structures in training datasets, these tools generated predicted CCS values with relatively large errors, introducing false positives/negatives during metabolite annotation. Alternatively, the curation of experimental CCS values from chemical standards is promising to achieve better performances in metabolite annotation. Compared with proteomics, error rate estimation  is under development in metabolomics. Recently, DIAMetAlyzer39 reported an automated false-discovery rate-controlled analysis for data-independent acquisition in metabolomics. More specifically for LC–IM–MS-based lipidomics, MS-DIAL reported the FDR of lipid annotations during RT and CCS matches using their validation set22. Sterol4DAnalyzer developed by our group also reported the FDR of sterols under different CCS match tolerances40. A comprehensive FDR estimation for 4D metabolomics annotation should include a ground-truth benchmark dataset and evaluations of all 4-dimensional matches with different tolerances, which would be an important future plan for 4D metabolomics.Currently, MS/MS spectrum is crucial for metabolite annotation and structural elucidation in untargeted metabolomics. Deciphering MS/MS spectral data through tandem spectral match with standard library, network-based strategies  and support all-in-one solution from raw data importing to metabolite annotation, like MS-DIAL, MZmine2O) were purchased from Honeywell . LC–MS grade acetonitrile (ACN) was purchased from Merck . Ammonium hydroxide (NH4OH) and ammonium acetate (NH4OAc) were purchased from Sigma-Aldrich . Metabolite chemical standards were purchased from Sigma-Aldrich , J&K , and Bidepharm . The NIST human urine (SRM 3667) and NIST human plasma (SRM 1950) sample were purchased from Ango Biotechnology . Chemical standards for 20 natural products were purchased from TopScience .LC–MS grade methanol (MeOH), 2-propanol (IPA), and water  were added into the dry extracts for reconstitution. The solution was vortexed for 30 s, sonicated at 4 °C for 10 min, and centrifuged at 17,000 × g and 4 °C. Finally, the supernatant was transferred into a vial for LC–IM–MS analysis. To prepare serially diluted urine samples, the final supernatant was directly diluted with ACN/H2O  by 10, 100, and 1000 folds, respectively. For NIST human plasma samples, 150 μL of plasma was taken and 600 μL of MeOH/ACN  was added for extraction. The rest procedures were kept the same as described for urine samples. The 293T cell line was obtained from ATCC with Product No. CRL-2925. The cells were cultured in 6-cm dishes with Dulbecco modified Eagle’s medium (DMEM) containing FBS (10%) and penicillin/streptomycin (1%). When growing to ~2,000,000 cells/dish, cells were harvested for metabolomics analysis. The culture medium was quickly removed and cells were washed with cold PBS twice. Dishes were placed on dry ice, and 1 mL of ACN/MeOH/H2O  was added for fast quenching and extraction. The extraction solution was pre-cooled at −80 °C for 1 h prior to the extraction. Then, dishes were incubated at −80 °C for 40 min. The cells were scraped from dishes and transferred to a 1.5-mL centrifuge tube. The samples were then vortexed for 1 min, and centrifugated for 15 min at 17,000 × g and 4 °C. The supernatant was collected and evaporated to dryness at 4 °C. For reconstitution, 100 μL of ACN/H2O  were added into the dry extracts. The rest of the procedure was kept the sample as described for NIST human urine samples. The preparation of mouse liver and brain tissues followed our previous publication43. The natural products were dissolved in MeOH with a concentration of 1 mg/mL as the stock solution. To prepare the natural products spiked-in NIST human urine sample with the highest concentration , we took 1 μL of each stock solution and spiked into 80 μL of reconstituted NIST human urine solution in ACN/H2O . Then, the 1X dilution sample was further diluted with reconstituted NIST human urine solution by 4, 16, 64, and 256 folds, respectively  and 25 mM ammonium acetate (NH4OAc) in water and mobile phase B of ACN were used, respectively. The gradient was set as below: 0–0.5 min: 95% B, 0.5–7 min: 95% B to 65% B, 7–8 min: 65% B to 40% B, 8–9 min: 40% B, 9–9.1 min: 40% B to 95% B, and 9.1–12 min: 95% B. The flow rate was 0.5 mL/min. The injection volume was 3 μL. For reverse phase (RP) separation, Phenomenex Kinetex C18 column  × 2.1 mm (i.d.)) was used and the column temperature was kept at 25 °C. For both positive and negative modes, mobile phase A of 0.01% acetic acid (v/v) in water and mobile phase B of IPA/ACN  were used, respectively. The gradient was set as below: 0–1 min: 1% B, 1–8 min: 1% B to 99% B, 8–9 min: 99% B, 9–9.1 min: 99% B to 1% B, 9.1–12 min: 1% B. The flow rate was 0.3 mL/min. The injection volume was 3 μL. For MS acquisition, PASEF-DDA scan mode was applied with mass range from 20 to 1300 Da and mobility range from 0.45 to 1.45 V·s/cm2. Detailed parameters for MS acquisition were set as follow: capillary voltages were set as +4500 V and −3600 V for positive and negative ionization modes, respectively; nebulizer pressure, 2.2 bar; dry gas, 10.0 L/min; dry temperature, 220 °C; number of PASEF MS/MS scans, 2; ramping time, 100 ms; TIMS stepping enabled; total cycle time, 0.53 s; charge range, 0–1; absolute threshold, 100 cts; active exclusion, checked; former target ions released after 0.1 min; isolation window, 1.2 Da; collision energy, 30 eV. In PASEF-DIA data acquisition, 7 mass steps with mass width of 144.3 Da and mass overlap of 5 Da were set in each cycle, covering the mass ranges of 20–1000 Da and mobility range of 0.45–1.45 V·s/cm2. The cycle time is 0.64 s. The data acquisition was performed using timsControl . For IM-AIF data acquisition in Agilent DTIM-MS, the source parameters were set as follows: sheath gas temperature, 325 °C; dry gas temperature, 300 °C; sheath gas flow, 11 L/min; dry gas flow, 8 L/min; capillary voltage, 4000 V; and nebulizer pressure, 20 psi. The TOF mass range was set as m/z 50–1700 Da. For ion mobility parameters, nitrogen (N2) was used for the drift gas. Other related IM parameters were set as follows: entrance and exit voltages of drift tube, 1600 and 250 V; trap filling and trap release times, 20,000 and 150 μs. The pressure of drift tube was set at 3.95 Torr. The MS/MS spectra were acquired in the “Alternating frames” mode, and the collision energy was fixed at 20 V in frame 2. The CCS values were calculated with single electric field method. Data acquisitions were carried out using MassHunter Workstation Data Acquisition Software .All metabolomics data were acquired using an UHPLC system  coupled to a timsTOF Pro equipped with an electrospray ionization (ESI) source  or DTIM-MS 6560 . For hydrophilic interaction liquid chromatography (HILIC) separation, Waters ACQUITY UPLC BEH Amide column  × 2.1 mm (i.d.)) was used for the LC separation and the column temperature was kept at 25 °C. For both positive and negative modes, mobile phase A of 25 mM ammonium hydroxide (NHhttps://www.genome.jp/kegg/) and HMDB  were combined and dereplicated with their InChIKey. Then, metabolites with exact masses larger than 1200 Da or less than 60 Da were removed. Compounds without available SMILES were removed. Finally, a total of 135,638 unique metabolites were generated as the Met4DX metabolite library  for calculation CCS values in different adduct forms13. Specifically, [M + H]+, [M + Na]+, [M + NH4]+ and [M + H-H2O]+ for positive mode, and [M-H]-, [M + Na-2H]-, [M + HCOO]- for negative mode were calculated, respectively.The SMILES strings of metabolites were inputted in our previous developed AllCCS  and reverse phase (RP) separations, respectively, covering a total of 1014 metabolites. For other metabolites, we employed a graph neural network (GNN)-based RT prediction model developed by Lu group for RT predictionhttps://mona.fiehnlab.ucdavis.edu/; accessed on 31 May, 2022) and NIST 20 mass spectral library, and dereplicated the spectra using InChIKey. A total of 5234 and 2784 metabolites had experimental MS2 spectra in positive and negative modes, respectively, covering 5506 metabolites. To predict MS2 spectra, in Met4DX, the candidate metabolites after MS1, RT, and CCS matches were further inputted into MS-FINDER (version 3.24) for prediction of MS2 spectra and MS2 spectral match (scoring and ranking).We first acquired the standard MS/MS spectra for 1064 metabolites with the same IM-MS parameters described in LC–IM–MS analysis part. In addition, we collected the experimental MS2 spectra in MoNA . For bins with more than 1 MS2 spectrum, 3D distances of all pairwise MS2 spectra were calculated by integrating the distances of precursor RT, mobility, and MS2 spectral similarity with Eqs. (i and j were the indexes of MS2 spectra in the bin and i ≠ j. The maximum tolerance (TOLmax) was the acceptable tolerance, while the minimum tolerance (TOLmin) was the penalty-free tolerance. Here, TOLmax and TOLmin were set as 10 s and 20 s for RT, and 0.015 and 0.030 V·s/cm2 for mobility, respectively. W was the weight in each dimension, and all weights were set as 1.For each data file, MS2 spectral dereplication was performed. Each MS2 spectrum was first purified by removing ions with intensities less than 30 and lower than 1%. Then, MS2 spectra were binned according to their differences of precursor ith Eqs. . The traThe bottom-up assembly algorithm for 4D peak detection48  and Bruker TDF-SDK  were used. After querying the raw data and extracting all MS1 frames, a 5-step 4D peak detection was implemented as follows:For each MS data file, Met4DX assembled the 4D peaks from its unique MS2 spectra with a bottom-up assembly strategy. To access raw data in.d format, the R package opentimsrm/z-ion mobility data frame with the precursor m/z, ion mobility, and frame index recorded in the .mgf file. Step 2: EIM detection. In the precursor frame, the adjacent MS1 data points within the set m/z and mobility ranges were retrieved to reconstruct the ion mobilogram. Specifically, m/z tolerance was 20 ppm or 0.004 Da for m/z < 200 Da, and the range to reconstruct ion mobilogram was set as 0.1 V·s/cm2 around the precursor MS1 data point. Then, the locally weighted scatterplot smoothing (LOESS) was applied for data smoothing. The EIM peak was detected by finding the local maximum within the peak span. The default peak span of EIM detection was 13 data points, converting to 0.013 V·s/cm2 under our instrument parameters. If multiple apexes found, the EIM peak with a smallest mobility difference to the precursor mobility was selected. Step 3: EIM extension. If EIM detection in step 2 was successfully achieved in the precursor frame, this step further extended EIM detection in 30 adjacent MS1 frames around precursor frames. Step 4: EIC detection. The EIM peaks in each frame were summed up to generate the frame intensities, which were further projected to the LC dimension. Thus, the ion chromatogram on LC dimension was assembled. After LOESS smoothing, the EIC peak was also detected by finding the local maximum within the peak span. The default peak span of EIC detection was 11 data points, converting to ~5.3 s in our experimental conditions. If multiple apexes found, the EIC with a smallest RT difference to the precursor RT was selected. Step 5: 4D integration. With the EIM peaks detected in step 2 and the EIC peak detected in step 4, the 4D peak was constructed. Met4DX integrated the ion intensities around the apexes. Specifically, the MS1 data points in 5 frames nearest to the EIC apex and within mobility differences of 0.015 V·s/cm2 to the EIM apexes were integrated. The m/z value of the 4D peak was re-weighted with the integrated MS1 data points’ m/z values and intensities.Step 1: precursor search. For each unique MS2 spectrum, Met4DX searched its precursor MS1 data point in the 2 were used, respectively. Additionally, there should be continuous signals near the apex. The signal-to-noise ratios (S/N) were also calculated to filter those signals with S/N lower than 3. Furthermore, noisy signals with high fluctuation  were also filtered, which followed our previous publication49.In 4D peak detection, a series of criteria were implemented to ensure the peak fidelity. During the EIM and EIC peak detection, the apexes should be the local maximum within the set span in accordance with the peak width at half height under our LC–IM–MS parameters. The detected apex should be within the tolerances of the precursor RT or mobility, respectively. Specifically, 10 s and 0.015 V·s/cmz was the ion charge and 1/K0 was the mobility. T is the temperature, 305 K. M and m are exact masses of the analyst ion and N2, respectively50.After the completion of the 4D peak detection, a 4D peak table was generated for each MS file. In this table, Met4DX calculated the CCS value of each feature from its experimental mobility with Eq. :7\docume4D peak alignment and groupingm/z, RT, CCS, and MS2 spectra). The reference sample was user-defined. We recommended using one of the pooled quality control (QC) samples or the middle sample in the injection order as the reference sample. Then, a RT correction model was built with RTs of landmarks using a LOESS-based strategy. The RTs in samples were corrected and aligned to the reference sample. After that, a density-based peak grouping strategy51 was implemented for feature grouping. 4D features across samples were binned together according to their m/z and mobility values. The bin sizes were set as 0.015 Da and 0.015 V·s/cm2. The density on RTs was profiled to generate the final 4D peak group. The bandwidth of gaussian smoothing was set as 5 s. The MS2 spectral stochasticity is common in DDA-based data acquisition. Met4DX re-performed the 4D peak detection in samples with missing peaks. The medium values of m/z and mobility among peaks in the peak group were used as the precursor information to perform the targeted 4D peak detection in samples with missing peaks. The MS1 frame with the smallest RT difference to the median of RTs in the peak groups was regarded as the precursor frame. The re-assembled 4D peaks should also meet the criteria of peak fidelity. Peak groups those met the requirement of minimal fraction  were kept. Gap filling was applied for missing values in the peak table through the mandatory integration, which integrated the signals in 5 frames, 20 ppm, and 0.015 V·s/cm2 in mobility near the RT, m/z, and mobility values of the 4D peak. Met4DX finally outputs the 4D peak table with the qualitative information of m/z, RT, and CCS as well as peak intensities in a.csv table, named “features_filled.csv”. MS2 spectra for features were also exported in a .msp file, named “spectra.msp”.We used a landmark-based strategy for RT alignment. The detected 4D peaks between one specific reference sample and other samples were matched with 4D information ))5)). The+ or [M-H]- adduct forms outputted by MS-FINDER. Finally, all metabolite annotation results outputted in a table named “ScoreCombine.csv”.For candidate metabolites without experimental MS2 spectra in the metabolite library, Met4DX exported the feature and its experimental MS2 spectrum into MS-FINDER for structural scoring and ranking. In Met4DX, it only kept the top 3 candidates in [M + H]The Met4DX workflow includes four major modules: (1) MS2 spectral dereplication; (2) the bottom-up assembly algorithm for 4D peak detection; (3) 4D peak alignment and grouping; (4) multidimensional match for metabolite identification.https://github.com/ZhuMetLab/Met4DX). Detailed parameters were provided in Supplementary Table m/z, RT, and CCS as well as peak intensities in a .csv table, named as “features_filled.csv”. MS2 spectra for 4D features were exported in a .msp file, named as “spectra.msp”. If metabolite annotation was performed, the multidimensional match result was outputted as a “ScoreCombine.csv” file. Met4DX also supported metabolite annotation with a user-defined metabolite library, and the instruction was provided in Supplementary Note For PASEF-DDA data, MS2 spectra in each raw MS file were first converted into the .mgf files using DataAnalysis . The raw MS data files and MS2 spectra in mgf files were organized into one folder and imported into Met4DX for data processing. If MS2 spectral files were not provided, Met4DX enabled to generate MS2 spectra directly from the raw data files using the “GenerateMS2” function. Our data showed that Met4DX showed high consistency in peak detection using MS2 spectra converted from DataAnalysis and generated by the “GenerateMS2” function . Then, Met4DX generated a 4D peak table after peak grouping which was further filtered with a minimal fraction (min. frac.) of 0.5. To assign MS2 spectra for each feature, Met4DX matched the precursor ion information  of an MS2 spectrum to those of 4D features, and selected the most intense MS2 spectrum. Finally, the gap-filling was performed in samples with missing values. Detailed parameters were provided in Supplementary Table For PASEF-DDA data, Met4DX also supports the input of a precursor ion list as seeds to initiate 4D peak detection. In Met4DX, we have curated a list of precursor ions collected from various biological samples . For each precursor ion, the bottom-up assembly algorithm was performed for 4D peak detection (see the workflow of Met4DX for details). Met4DX generated a 4D peak table after peak grouping, which was further filtered with a minimal fraction (min. frac.) of 0.5. The extraction of MS2 spectra at apex of retention time and drift time was also performed to assign MS2 spectra to each 4D peak. Finally, the gap-filling was performed in samples with missing values. Detailed parameters were provided in Supplementary Table For Agilent IM-AIF data, raw data files (.d format) were first converted into .mzML format with ProteoWizard (version 3.0.20360). Then, Met4DX converted CCS values in the precursor ion list into drift times with CCS calibration coefficients , raw data files were first converted into .ibf format with IbfConverter.exe. Then, MS-DIAL performed peak detection, alignment, gap filling, and MS2 spectral assignment with the converted data files. Detailed parameters were provided in Supplementary Table 26. Specifically, in MS-DIAL and MetaboScape, we used the feature information from their feature tables to re-extract the 4D features for peak fidelity evaluation. The peak fidelity rates were calculated with these re-extracted 4D features (Supplementary Fig. For each 4D feature with MS2 spectra from Met4DX, MS-DIAL, and MetaboScape, we selected the replicate sample with the highest intensity, and then assembled the 4D peak in this replicate sample to obtain the EIC and EIM peaks and evaluate the peak fidelity of the feature. For EIC peaks, the IM dimension was removed, while for EIM peaks, the LC dimension was removed. The EIC and EIM peak shapes were inputted into the EVA software for peak fidelity evaluationFurther information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Supplementary Data 7Supplementary Data 8Supplementary Data 9Supplementary Data 10Supplementary Data 11Supplementary Data 12Reporting Summary


Candida albicans clinical isolates, including standard lab strain SC5314, exhibited temperature-enhanced tolerance at 37°C and 39°C, and were not tolerant at 30°C. Other isolates were either always tolerant (23.3%) or never tolerant (7.5%) at these three temperatures, suggesting that tolerance requires different physiological processes in different isolates. At supra-MIC fluconazole concentrations (8 to 128 μg/mL), tolerant colonies emerged rapidly at a frequency of ~10−3. In liquid passages over a broader range of fluconazole concentrations (0.25 to 128 μg/mL), tolerance emerged rapidly (within one passage) at supra-MICs. In contrast, resistance appeared at sub-MICs after 5 or more passages. Of 155 adaptors that evolved higher tolerance, all carried one of several recurrent aneuploid chromosomes, often including chromosome R, alone or in combination with other chromosomes. Furthermore, loss of these recurrent aneuploidies was associated with a loss of acquired tolerance, indicating that specific aneuploidies confer fluconazole tolerance. Thus, genetic background and physiology and the degree of drug stress (above or below the MIC) influence the evolutionary trajectories and dynamics with which antifungal drug resistance or tolerance emerges.Antifungal drug tolerance is a response distinct from resistance, in which cells grow slowly above the MIC. Here, we found that the majority (69.2%) of 133  Candida, Aspergillus, and Cryptococcus  temperature-elevated tolerance (TET) at 37 and 39°C, relative to 30°C, and (ii) all-temperature tolerant (ATT) and (iii) never-tolerant (NT) isolates at the three temperatures. We then evolved representative TET and ATT isolates for adaptation to FLC at a range of drug concentrations. We found that aneuploidy appears rapidly and is associated with increased tolerance, especially at drug concentrations above the MIC. In contrast, resistant isolates emerged at sub-MIC drug concentrations, only after ~5 days of passaging in sub-MIC drug concentrations, and they proceeded to acquire higher resistance levels with time. Some of the resistant adaptors also acquired aneuploidies, but different ones from those in tolerant adaptors. This suggests that tolerance and resistance appear with distinct evolutionary dynamics and trajectories.In this study, we first screened a collection of 133 clinical isolates to determine the prevalence of FLC tolerance under Previously, we found that temperature and medium composition each affected antifungal tolerance to FLC and ketoconazole , 13. The10.1128/mbio.00227-23.1FIG S1C. albicans lab strain SC5314 was tested on disk diffusion assays with drug disks (25 μg FLC) on agar plates containing the indicated medium and grown at the indicated temperatures. The plates were photographed at 48 h to highlight tolerance (growth within the zone of inhibition). Download FIG S1, TIF file, 1.9 MB.Physiological factors affect fluconazole tolerance. Copyright © 2023 Yang et al.2023Yang et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the C. albicans isolates for their susceptibility/resistance and tolerance levels in YPD medium under standard lab conditions (30°C) and at normal (37°C) and febrile (39°C) human body temperatures. We used disk diffusion assays analyzed by diskImageR (20]) and the tolerance (as the fraction of growth [FoG20] in the zone of inhibition relative to growth outside it) for each strain. For most strains (69.2%), tolerance levels were affected by temperature, with higher tolerance levels at 37°C and 39°C than at 30°C, and little difference between tolerance levels measured at 37°C and those at 39°C : temperature-enhanced tolerant (TET) ; all-temperature tolerant (ATT), which had similar FoG20 values at all three temperatures ; and nontolerant (NT), which exhibited only baseline levels of FoG20 at all three temperatures . At 37°C and 39°C, 92.5% (123 out of 133) of the strains exhibited similar tolerance levels, while at 30°C, 76.7% (102 out of 133) were not tolerant on the YPD medium  for TET, YJB-T1891 for ATT, and YJB-T490 for NT strain classes. The three isolates had the same MIC value (1 μg/mL) at 30°C, 37°C, and 39°C on YPD , while at 37°C, growth was detectable. Colonies of the ATT isolate (YJB-T1891) grew at both 30°C and 37°C in all FLC concentrations, regardless of the MIC (1 μg/mL) , and forScanLag also measures colony growth on agar and reports the time required for a colony to become detectable on the plate. This time of appearance is considered a proxy of lag phase length  at 30°C and 37°C on the same range of FLC concentrations. As expected, all controls produced a lawn of cells. In contrast, the TET strain at 30°C and the NT strain at both temperatures gave rise to a few hundred to a few thousand colonies (adaptors) per plate after 5 days on the drug plates , ATT (YJB-T1891), and NT (YJB-T490) strains were grown on YPD plates supplemented with FLC at the indicated concentrations and incubated at 30°C and 37°C for 5 days. Estimated numbers of colonies on plates with 8 μg/mL to ~128 μg/mL drug are also shown. Download FIG S2, TIF file, 2.5 MB.Growth of tolerant and nontolerant strains on fluconazole plates. Approximately 1 × 10Copyright © 2023 Yang et al.2023Yang et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the temperature-sensitive tolerance (TST) seen only at 30°C and not at 37°C; when evolved at 37°C, NT isolates acquired tolerance that was detectable at both 30°C and 37°C, a phenotype akin to that of other ATT-like adaptors.Disk diffusion assays were then performed on 90 randomly selected adaptors from SC5314 and YJB-T490 parent strains (18 adaptors from each 30°C drug plate). All these adaptors had a notable elevated tolerance  when tesTo identify genomic mechanisms by which the SC5314- and YJB-T490-derived adaptors acquired tolerance, we performed deep sequencing of 18 independent adapted isolates for the TET and NT strains collected at 30°C on 8, 32, and 128 μg/mL of FLC. Taken together, 54 adaptors derived at 30°C from TET and NT isolates were sequenced.de novo single nucleotide polymorphisms (SNPs)  . Other mutations were all unique to a single adaptor: four of the remaining SNPs were in genes encoding proteins with unknown functions. None of the remaining 6 genes encodes any functions known to directly or indirectly affect drug responses . Mutation in one of the genes, PGA63, is similar to Saccharomyces cerevisiaeSEC31, which is annotated as having increased tolerance for aneuploid chromosomes , which appeared on the 8 μg/mL FLC plate, grew poorly and was excluded from sequencing and further analysis. From the others, 50 (94.3%) were aneuploid  and thredaptors) . Among tomosomes , but the10.1128/mbio.00227-23.3FIG S3FIG S3, PDF file, 1.6 MB.Karyotypes of all adaptors evolved from SC5314 at 30°C. SC5314-derived adaptors from YPD plates supplemented with 8 μg/mL, 32 μg/mL, and 128 μg/mL were deep sequenced, and karyotype maps were generated by using Ymap. Each chromosome is illustrated to scale. The centromere positions are indicated by an indentation. The major repeat sequence (MRS) positions are indicated by a black square below the chromosome. Local copy number estimates, scaled to the genome ploidy, are displayed as black histograms along the length of the chromosome. Allele frequencies are color coded: homolog “a” is cyan, homolog “b” is magenta, and heterozygous alleles are gray. Karyotypes of all the adaptors sequenced are shown. The order of the adaptors is the same as the order in which they were picked up from the fluconazole plates. Download Copyright © 2023 Yang et al.2023Yang et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 10.1128/mbio.00227-23.4FIG S4FIG S4, PDF file, 1.6 MB.Karyotypes of adaptors derived from NT strain YJB-T490 at 30°C. YJB-T490-derived adaptors chosen from YPD plates supplemented with 8 μg/mL, 32 μg/mL, and 128 μg/mL at 30°C were deep sequenced. Karyotypes of all the 54 adaptors sequenced are shown. Homozygosis of alleles is indicated in red. Download Copyright © 2023 Yang et al.2023Yang et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 10.1128/mbio.00227-23.7TABLE S1Table S1, PDF file, 0.06 MB.Mutations detected in coding sequences in 5 euploid fluconazole-tolerant adaptors. Download Copyright © 2023 Yang et al.2023Yang et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the Analysis of adaptor karyotypes revealed several recurrent aneuploidies, several of which were seen in both the TET- and NT-derived isolates. The most prevalent adaptors  had aneuploidy involving ChrR, either as trisomy of the whole chromosome (ChrRx3) , monosomy of the left arm distal to the ribosomal DNA (rDNA) repeats (SegChrRx1) (6 from TET), or trisomy of ChrR from rDNA repeats to the right telomere (SegChrRx3) (12 from NT), or a combination of SegChrRx3 and SegChrRx1 (10 from TET). These ChrR aneuploidies appeared alone or in combination with trisomy of another chromosome(s)  . Five TEOverall, next-generation sequencing (NGS) revealed 21 different karyotypes among the 50 TET-derived ATT-like aneuploid adaptors and 17 different karyotypes among the 53 NT-derived TST aneuploid adaptors. Despite differences in genetic background and FLC concentration used for selection, the same aneuploidies (predominantly ChrRx3 or SegChrRx3) were recurrently associated with the emergence of FLC tolerance. This occurred in both the ATT types derived from TET ancestral isolates and the TST types derived from NT ancestral isolates.n = 1) or in combination with aneuploidy (mostly trisomy) of one or more other chromosomes (n = 6). Only two NT→ATT adaptors did not have Chr6 aneuploidy: one adaptor had SegChr1x1 alone, and one had SegChr2x1 alone.The NT-derived adaptors obtained at 37°C also had diverse karyotypes. Each of the nine sequenced NT→ATT adaptors had a unique karyotype that was not seen in the NT→TST adaptors obtained at 30°C : 7 had aTaken together, the karyotypes of the adaptors were FLC dose independent but temperature dependent. At 30°C, the TET- and NT-derived karyotypes involved recurrent ChrR amplification in TET→ATT and NT→TST adaptors selected across the range of FLC concentrations used. In contrast, from selection at 37°C, NT→ATT adaptors had distinctly different aneuploidy: predominantly Chr6 trisomy and tetrasomy, alone or in combination with another aneuploid chromosome. Thus, selection at 30°C yielded similar karyotypes with different tolerance temperature responses in different strain backgrounds. Moreover, different selection temperature (30°C versus 37°C) yielded different karyotypes in the same strain background (NT→TST versus NT→ATT)  and 4.C. albicans  that passed our quality filters  in the small (aneuploid) and large colonies of the tolerant adaptors . Small a10.1128/mbio.00227-23.8TABLE S2Table S2, PDF file, 0.4 MB.Mutations detected in coding sequences in 6 pairs of small and large colonies. Download Copyright © 2023 Yang et al.2023Yang et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the Importantly, all the small colonies retained the higher tolerance seen in their parent strain and remained aneuploid like the adaptors from which they were derived. In contrast, all the large colonies were no longer tolerant  and had 19–Because the TET and NT isolates acquired tolerance, but not resistance, when exposed to supra-MICs of FLC on solid medium, we next asked if this was a function of the FLC concentration. We evolved one TET isolate (SC5314) and one NT isolate (YJB-T490) by passaging them daily  in YPD broth supplemented with FLC ranging from 4× below the MIC (0.25 μg/mL) to 128× above the MIC (128 μg/mL) for a total of 15 days. As a control, we also passaged the isolates in YPD without drug.Every 5 days we randomly selected 18 or 96 colonies from the TET and NT cultures, respectively. In total, we measured 18 and 96 TET and NT derivatives per day  and per drug concentration  for a total of 792 (SC5314 derivatives) and 4,224 (YJB-T490 derivatives) measurements, respectively  and B.20), while none of the adaptors acquired increased FLC resistance , most of the 2,688 adaptors evolved at supra-MICs (2 to 128 μg/mL) exhibited tolerance, and none exhibited resistance (For SC5314 (MIC of ~1 μg/mL FLC), among the 504 adaptors evolved at supra-MICs (2 to 128 μg/mL FLC), most exhibited tolerance  after 5 and 10 passages, while only resistant isolates appeared after 15 days of passaging at the MIC. Thus, it appears that at the MIC, SC5314 adaptors that were tolerant after 5 and 10 passages became resistant after 15 passages. Furthermore, there was a stepwise increase in the level of resistance in adaptors evolved for 5, 10, and 15 days in 1 μg/mL FLC . For YJB10.1128/mbio.00227-23.5FIG S5FIG S5, TIF file, 2.3 MB.Stepwise increase in MICs for resistant adaptors evolved in 1 μg/mL fluconazole. On day 5, day 10, and day 15, the MIC of one resistant adaptor from the 1-μg/mL cultures was tested with FLC Etest strips. As a control, the parent and one adaptor isolated from passage 1 were also tested. The plates were incubated at 30°C for 48 h and then photographed. Download Copyright © 2023 Yang et al.2023Yang et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 20) or tolerant (increased FoG20) (but not both). Among the adaptors evolved in 0.25 μg/mL and 0.5 μg/mL FLC, resistance emerged in 35 and 30 adaptors, respectively, while tolerance was detected in 1 and 6 adaptors, respectively. The remaining adaptors appear to have had more transient tolerance that had been lost during growth in the absence of FLC. Adaptors evolved for 10 and 15 days in 0.5 μg/mL FLC also exhibited stepwise increases in resistance. YJB-T490 adaptors also acquired either resistance or tolerance (but not both). Among adaptors evolved in 0.25 μg/mL FLC, tolerance appeared after 10 passages; yet after 15 passages in 0.25 μg/mL FLC for 15 days, 10 were tolerant, and 23 were resistant. At 0.5 μg/mL, the proportion of resistant YJB-T490 adaptors relative to tolerant adaptors increased over time 0 versus 58, 29 versus 18, and 72 versus 24, for adaptors from passages 5, 10, and 15, respectively (At sub-MICs (0.25 and 0.5 μg/mL), SC5314 adaptors became either resistant  and with different temporal dynamics , and tolIndividual colonies that arose following the evolution of SC5314 in broth passages had a range of resistance or tolerance levels, suggesting that they may have acquired distinct genetic or genomic changes. To test this hypothesis, we sequenced 73 randomly selected adaptors (34 resistant and 39 tolerant) derived from SC5314. Large-scale genome changes were visualized with Ymap , and var10.1128/mbio.00227-23.6FIG S6FIG S6, PDF file, 0.8 MB.Karyotypes of progeny evolved in YPD broth supplemented with fluconazole. Thirty-four FLC-resistant and 39 FLC-tolerant progeny were sequenced. FLC concentration and time point of test are indicated above each section. Strain name and whether it exhibited resistance (R) or tolerance (T) are indicated to the left of each karyotype. Download Copyright © 2023 Yang et al.2023Yang et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the n = 9), SegChrRx3 from 1.89 Mb to right telomere (n = 3), or SegChrRx1 from 1.89 Mb to right telomere (n = 1). An additional 25 adaptors were aneuploid for ChrR in combination with aneuploidy of another one or two chromosomes . Only one tolerant adaptor  did not include copy number changes on ChrR. Thus, ChrR aneuploidy was the most prevalent aneuploidy associated with tolerance.Notably, all 39 tolerant adaptors that were sequenced were aneuploid  were euploid and 12 were aneuploid. Among the aneuploid adaptors, two (SY60 and SY61) had Chr3x3, five  had Chr5x3, four  had Chr7x3 (AAB), and one adaptor (SY57) had Chr6x3 (AAB) together with Chr7x3 (AAB). Notably, none of the resistant adaptors affected ChrR copy number, and the karyotypes of the resistant adaptors were distinct from the tolerant adaptors . TherefoImportantly, similar types of karyotypes were detected in SC5314- and YJB-T490-derived tolerant adaptors selected on supra-MIC FLC concentrations on agar plates  and S4. S. cerevisiaeDPB11, which, when mutated, causes gross chromosomal rearrangements, chromosome loss, and an increase in spontaneous DNA damage , but none were in genes that encode efflux pumps, or that are known to affect ergosterol biosynthesis, the two major mechanisms of azole resistance. We suggest that some of these SNPs are probably neutral or nearly neutral mutations that arose during the course of passaging and/or false-positive variants that our quality filters were not stringent enough to filter out.C. albicans, a common cause of systemic bloodstream infections, primarily acquired tolerance to the widely used drug FLC. Importantly, this antifungal tolerance appeared rapidly, in some cases within a single day of exposure to drug concentrations above the strain MIC, while resistant isolates appeared after 5 days of exposure to low levels of FLC. Furthermore, the resistant isolates exhibited a stepwise increase in MIC levels  from different combinations of aneuploid chromosomes that provide a growth advantage in supra-MIC drug concentrations. Even though we detected a few SNPs in the aneuploid isolates and we do not know the degree to which they may (or may not) contribute to tolerance, the fact that loss of the aneuploid chromosome(s) was accompanied by loss of FLC tolerance suggests that aneuploidy was the primary mechanism conferring tolerance. The mechanism(s) by which the 5 euploid adaptors became FLC tolerant is less clear as the few SNPs identified in these strains did not encode obvious mediators of drug efflux, stress response, or alternative strategies to bypass the deleterious effects of ergosterol depletion due to FLC exposure. While the SNPs or some other unidentified genetic change cannot be ruled out, another possibility is that nongenetic metabolic shifts contributed to the ability of these isolates to grow despite the presence of supra-MIC drug concentrations .Strain background and environmental conditions also contribute to the selective conditions that favor the acquisition of different aneuploidies. Interestingly, in both the TET and NT backgrounds, amplification of portions of ChrR enabled tolerance at 30°C but not at 37°C. Yet, for the NT strain, Chr6 trisomy increased tolerance at both 30°C and 37°C in the presence of the same range of FLC concentrations. Thus, the rapid emergence of tolerance can occur via multiple routes, and the trajectories of the routes are affected by the original strain background and the selection conditions. Future work will require analyzing the trajectories of adaptation of additional TET and NT isolates and identifying the chromosomal region(s) that specifically affects tolerance at different temperatures.20). This was also seen for isolates passaged in posaconazole, another fungistatic azole  following exposure to supra-MIC drug concentrations? We suggest that three forces drive the rapid appearance of aneuploidy at high frequency: first, random aneuploid chromosomes maintained in the parent population may provide standing variation; second, FLC induces chromosome missegregation via cell cycle defects that yield tetraploid intermediates and, subsequently, random aneuploids , it follows that a single aneuploid chromosome should affect the stoichiometry of many proteins. Since segmental aneuploidies, which are dependent upon recombination events, also appeared, it is tempting to speculate either that drug stress increases the likelihood of mitotic recombination, as was seen for loss-of-heterozygosity (LOH) events . Since ) events , or thattability .In this study, tolerant adaptors emerged more rapidly (within one passage) than resistant adaptors. Ultimately, all supra-MIC isolates became tolerant, while only some of the sub-MIC adaptors became resistant. Indeed, even resistant adaptors that had acquired resistance via aneuploidy appeared much later in the passaging and may have arisen from tolerant intermediates . Thus, C. albicans, two major mechanisms contribute to FLC resistance: alteration of the drug target and increased drug efflux. A combination of these mechanisms causes stepwise development of FLC resistance  agar medium  at 30°C. Other media used in this study include Casitone agar plates , SD agar plates , and SDC agar plates . Drugs were dissolved in dimethyl sulfoxide (DMSO) and stored at −20°C.Strains used in this study are listed in 10.1128/mbio.00227-23.10TABLE S4Table S4, DOCX file, 0.02 MB.Strains used in this study. Download Copyright © 2023 Yang et al.2023Yang et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 6 cells/mL, and 100 μL of the culture was spread on YPD agar. The plate with an FLC Etest strip  at the center was incubated at the designated temperature for 24 h and then photographed.Etest assays were performed as described previously . Strains6 cells/mL. One hundred microliters of cell suspension was spread onto 15-mL YPD plates. An empty paper disk (6-mm diameter and 0.7-mm thickness) supplemented with 5 μL of 5 mg/mL FLC was placed in the center of each plate. Plates were then incubated at designated temperatures and photographed at 24 h and 48 h. Analysis of the disk diffusion assay was done using the diskImageR pipeline .Disk diffusion assays were performed as previously described , 13. Thepipeline . The fra7 cells/mL. Three microliters of 10-fold serial dilutions was spotted on YPD plates with or without drugs (control). The plates were incubated at the designated temperature and photographed after 2 days.Cells were suspended in distilled water and counted using a hemocytometer. Cell density was adjusted to 1 × 10The ScanLag assay was performed as described in reference 7 cells/mL as described above. One hundred microliters of the culture was spread on YPD plates supplemented with drugs. The plates were incubated at the designated temperature for 5 days. Adaptors were randomly chosen.Cells were adjusted to 1 × 103 cells/mL. The YPD broth was supplemented with DMSO (negative control) or with a 2-fold increase of FLC from 0.25 μg/mL to 128 μg/mL FLC. Every 24 h or when the optical density at 600 nm (OD600) of culture was higher than 1.0, 1 μL of each culture was inoculated into 1 mL YPD broth supplemented with the same concentration of FLC. After 1, 5, 10, and 15 days, the cultures were washed and diluted with distilled water. Approximately 100 cells were spread on YPD plates. The plates were incubated at 30°C for 36 h, and 18 colonies from each plate were randomly tested with disk diffusion assays using FLC-containing disks.SC5314 was inoculated into 1 mL YPD broth at a final density of approximately 2.5 × 10As described previously , aneuploNext-generation sequencing (NGS) was performed as described in reference C. albicans reference genome (GCF_000182965.3_ASM18296v3) with Burrows-Wheeler Aligner  (http://broadinstitute.github.io/picard/). Indels were then realigned with GATK (version 3.8-1-0)   with def 0.7.17) . The ali 0.7.17) , and dup3.8-1-0) , and the3.8-1-0) . Variant3.8-1-0) , filtere3.8-1-0) . The val3.8-1-0) .http://www.candidagenome.org/cgi-bin/GO/goTermFinder) was used for functional enrichment analysis, using default parameters. Only hits with a P value corrected for false positives (FDR) of <0.1 were considered significant.The Gene Ontology Term Finder tool on the Candida Genome Database (www.ebi.ac.uk/arrayexpress) under accession numbers E-MTAB-12175, E-MTAB-12155, E-MTAB-12169, and E-MTAB-12189.All sequence data are available in the ArrayExpress database at EMBL-EBI (