Phosphoproteomic and transcriptomic analyses reveal multiple functions for Aspergillus nidulans MpkA independent of cell wall stress

Accepted Manuscript Phosphoproteomic and transcriptomic analyses reveal multiple functions for Aspergillus nidulans MpkA independent of cell wall stress Cynthia L. Chelius, Liliane F.C. Ribeiro, Walker Huso, Jyothi Kumar, Stephen Lincoln, Bao Tran, Young Ah Goo, Ranjan Srivastava, Steven D. Harris, Mark R. Marten PII: DOI: Reference:

S1087-1845(18)30174-9 https://doi.org/10.1016/j.fgb.2019.01.003 YFGBI 3184

To appear in:

Fungal Genetics and Biology

Received Date: Revised Date: Accepted Date:

4 September 2018 18 December 2018 4 January 2019

Please cite this article as: Chelius, C.L., Ribeiro, L.F.C., Huso, W., Kumar, J., Lincoln, S., Tran, B., Ah Goo, Y., Srivastava, R., Harris, S.D., Marten, M.R., Phosphoproteomic and transcriptomic analyses reveal multiple functions for Aspergillus nidulans MpkA independent of cell wall stress, Fungal Genetics and Biology (2019), doi: https:// doi.org/10.1016/j.fgb.2019.01.003

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Phosphoproteomic and transcriptomic analyses reveal multiple functions for Aspergillus nidulans MpkA independent of cell wall stress Cynthia L. Cheliusa, Liliane F.C. Ribeiroa, Walker Husoa, Jyothi Kumarb, Stephen Lincolnc, Bao Trand,1, Young Ah Good,2, Ranjan Srivastavac, Steven D. Harrisb,3, Mark R. Martena. a. Department of Chemical, Biochemical, and Environmental Engineering, University of Maryland Baltimore County, Baltimore, MD 21250 b. Center for Plant Science Innovation and Department of Plant Pathology, University of Nebraska-Lincoln, Lincoln, NE 68588 c. Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, CT 06269 d. Mass Spectrometry Center, University of Maryland School of Pharmacy, Baltimore, MD, 21201 1 current address: The U.S. Army CBRNE Analytical and Remediation Activity Laboratory, The 20th CBRNE Command, Aberdeen Proving Ground, MD 21005 2 current address: Northwestern Proteomics Center, Northwestern University, Chicago, IL 60611 3 current address: Department of Biological Sciences, University of Manitoba, Winnipeg, MB, Canada R3T 2N2

Key Words: Aspergillus nidulans, MpkA, multi-omics, cell wall, iron regulation, branching

Prepared for Submission to: Fungal Genetics and Biology

Corresponding Author: Mark R. Marten Engineering, Room 314 1000 Hilltop Circle Baltimore, MD 21250 410-455-3439 [email protected]

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ABSTRACT The protein kinase MpkA plays a prominent role in the cell wall integrity signaling (CWIS) pathway, acting as the terminal MAPK activating expression of genes which encode cell wall biosynthetic enzymes and other repair functions. Numerous studies focus on MpkA function during cell wall perturbation. Here, we focus on the role MpkA plays outside of cell wall stress, during steady state growth. In an effort to seek other, as yet unknown, connections to this pathway, an mpkA deletion mutant (ΔmpkA) was subjected to phosphoproteomic and transcriptomic analysis. When compared to the control (isogenic parent of ΔmpkA), there is strong evidence suggesting MpkA is involved with maintaining cell wall strength, branching regulation, and the iron starvation pathway, among others. Particle-size analysis during shake flask growth revealed ΔmpkA mycelia were about 4 times smaller than the control strain and more than 90 cell wall related genes show significantly altered expression levels. The deletion mutant had a significantly higher branching rate than the control and phosphoproteomic results show putative branching-regulation proteins, such as CotA, LagA, and Cdc24, have a significantly different level of phosphorylation. When grown in iron limited conditions, ΔmpkA had no difference in growth rate or production of siderophores, whereas the control strain showed decreased growth rate and increased siderophore production. Transcriptomic data revealed over 25 iron related genes with altered transcript levels. Results suggest MpkA is involved with regulation of broad cellular functions in the absence of stress. 1. Introduction Filamentous fungi are both industrially relevant and medically significant microorganisms. Whereas various species are beneficial, such as those used to produce enzymes, pharmaceuticals, and food additives (Grimm et al., 2005), other pathogenic species are responsible for more than 1.5 million deaths per year (Brown et al., 2013). In both cases, the fungal cell wall plays a dramatically important role. During industrial fermentations, cell wall tensile strength impacts hyphal fragmentation, which influences fungal morphology, oxygen transfer, viscosity, and even productivity (Li et al., 2002). In pathogens, the cell wall contributes to virulence by allowing fungi to evade host defense recognition (Fujikawa et al., 2012). Additionally, the cell wall is a high priority therapeutic target in pathogenic species because it is a unique feature of fungi that is not conserved in humans (Mircus et al., 2009). To increase our understanding of filamentous fungal cell walls, we focus here on the model species Aspergillus nidulans and study the cell wall integrity pathway. In general, filamentous fungal cell walls are primarily comprised of: α-(1,3)-glucan, β-(1,3)glucan, β-(1,6)-glucan, chitin, and galactomannans (Riquelme, 2013). These components are assembled in a composite-like structure and are responsible for protecting fungi from environmental and mechanical stresses while maintaining cell shape. In A. nidulans, the cell wall integrity signaling (CWIS) pathway is responsible for the remodeling and repair of damaged cell walls (Yoshimi et al., 2013). Fujioka et al. determined that the CWIS MAPK cascade (MkkABckA-MpkA) is responsible for regulating just α-(1,3)-glucan synthase genes (agsA and agsB ) (Fujioka et al., 2007). Outside of the conserved CWIS pathway, other studies have found MpkB (Yoshimi et al., 2015), WscA and WscB (Futagami and Goto, 2012), MtlA (Futagami et al., 2014), PmtA, PmtB, and PmtC (Kriangkripipat and Momany, 2009), and PmrA and PmcA (Jiang 2

et al., 2014) are involved in regulating cell wall repair genes. It remains unclear how the other important cell wall related genes are regulated. Gene regulatory networks are often highly complex, interconnected webs of G-proteins, kinases, transcription factors, scaffold proteins, and other enzymes (Qi and Elion, 2005). Various kinases play a primary role in many of these networks and often have multiple functions within the cell. MpkA is an integral component of the CWIS pathway and the observation that deletion of mpkA results in aberrant hyphal and colony morphology (Bussink and Osmani, 1999) strongly suggests that CWIS is connected to fungal morphology through MpkA. To study the various roles of MpkA in A. nidulans, we used a quantitative mass-spectrometry based phosphoproteomic approach to compare global changes in protein phosphorylation between an A. nidulans mpkA deletion mutant (ΔmpkA) and its isogenic parent. We combined these data with RNA-sequencing data in an attempt to better understand the downstream effects of mpkA disruption on gene expression. Utilizing a global, multi-omic approach reveals previously unknown MpkA functions outside of cell wall stress. 2. Materials and methods 2.1 Cell Strains and Growth Aspergillus nidulans strains A1405 (Control) and A1404 (ΔmpkA) (Fungal Genetic Stock Center, Manhattan, KS) were grown up on MAGV agar plates (2.0% (w/v) malt extract, 1.5% (w/v) agar, 0.2% (w/v) peptone, and 2.0% (w/v) glucose, 0.1% (v/v) Hutner’s trace elements and 0.1% (v/v) vitamin solution) for two days at 28⁰ C. For shake flask experiments, fresh spore lawns were harvested and 1x107 spores were inoculated into 50mL of low pH YGV (0.5% (w/v) yeast extract, 2.0% (w/v) glucose, 0.1% (v/v) Hutner’s trace elements and 0.1% (v/v) vitamin solution, pH adjusted to 3.3 with 1M HCl). After 12 hours growth, flasks were used to seed 1.2L of YGV media (pH 6.5) in a 2.8L Fernbach flask. All flasks were subjected to shaking at 250rpm and 28⁰ C. 2.2 Sample preparation for phosphoproteomic analysis Two biological replicates of control strain and ΔmpkA were grown as described above. Mycelia were harvested after 20 hours of growth by passing broth through miracloth and immediately freezing biomass in liquid nitrogen. Mycelia were crushed by mortar and pestle with liquid nitrogen into a fine powder and RIPA buffer (Thermo Fisher Scientific, Waltham, MA) was added to crushed cells (1:1 v/v). Protein concentration of the supernatant was established by BCA assay (Pierce, Rockford, IL). The Filter Aided Sample Preparation (FASP) protocol adapted from Wisniewski et al. was used to digest protein (Wisniewski et al., 2009). Briefly, 500 micrograms protein was precipitated with ice cold 20% TCA (1:1 v/v) for 1 hour. The protein pellet was washed twice with 500μL ice cold acetone, re-suspended in 1.25 mL of freshly prepared buffer (7.5mM TCEP + 8M Urea + 100mm NH4HCO3), and loaded into 3kDa MWCO centrifugal filters (Millipore, Billerica, MA) at 37⁰ C for one hour. Following incubation and centrifugation, alkylation buffer (250μL of 8M 3

Urea + 100mM NH4HCO3 + 50mM Iodoacteamide) was added to the protein solution and left in the dark for one hour at room temperature. After removing buffer by centrifugation, 25μL of 500mM DTT was added to residual alkylation buffer and then washed four times with 300μL of 50mM NH4HCO3. Sample were collected and Trypsin Gold (Promega, Madison, WI) (50μg protein:1μg trypsin) was added for digestion overnight in a 37⁰ C. The samples were acidified with TFA obtaining a pH < 2 prior to being lyophilized to dryness. Dried peptides were then subjected to TiO2 affinity chromatography for phosphopeptide enrichment using a protocol Magdeldin et al. slightly adapted from the Pierce TiO2 Phosphopeptide Enrichment and Clean-up Kit (Pierce, Rockford, IL) protocol (Magdeldin et al., 2014). Following enrichment and cleanup, the phospho-enriched samples were dried to completeness and stored at -80⁰ C until mass spectrometry analysis. 2.3 Liquid chromatography - Mass Spectrometry and Label Free Quantification Analysis Lyophilized peptides were reconstituted in 5% acetonitrile/0.1% formic acid for LC-MS/MS analysis. Samples were run in triplicate on a nanoAcquity LC (Waters, Milford, MA) coupled to an Orbitrap Fusion Tribrid mass spectrometer (Thermo Scientific, San Jose, CA). Peptides were trapped on a 100μm i.d. x 2 cm, which was in-house packed with 200Å, 5μm C18AQ particles (Michrom BioResources Inc., Auburn, CA, USA), and separated on a 75μm i.d. x 18 cm, which was pulled using a Sutter Instruments P-2000 CO2 laser puller (Sutter Instrument Company, Novato, CA) and packed with 100 Å, 5 µm C18AQ particles, at a flow rate of 250nL/min. Mobile phase A was 0.1% formic acid in water and mobile phase B was 0.1% formic acid in acetonitrile. For each injection, approximately 1-2μg of sample was loaded on the pre-column at 4 μl/minutes for 10 minutes using loading buffer of 5% acetonitrile and 0.1% formic acid. Peptide separation was performed at 250 nL/minute flow rate using a 95 minute gradient profile: 5-35% B in 60 min, 35-90% B in 10min, 90-90% B in 5min and 5-5% B in 20min. Mass spectrometry data were collected in positive ionization mode using a data dependent acquisition method with a full MS scan for m/z range 350-2000 in orbitrap at 120K resolution. Consecutive MS/MS scans were performed in the ion trap by top-speed decision selection with a dynamic exclusion of 30 seconds. Precursor ions selected from the first MS scan were isolated with an isolation width of 2 m/z for collision induced dissociation (CID) energy and normalized collision energy (NCE) set to 35. All LC-MS/MS data was processed with MaxQuant software version 1.5.3.17 (Cox et al., 2011) against a UniprotKB database containing 10,555 A. nidulans protein sequences. The following software parameters were used: a fixed modification of carbamidomethyl (C), dynamic modifications of acetylation (N-terminus), oxidation (M), phosphorylation (STY), and maximum missed cleavages of 2. Peptide spectrum matches (PSM) were filtered at a false discovery rate of 0.01 and protein identification was determined at FDR of 0.01. 2.4 Post phosphorylation site quantification analysis MaxQuant file “Phospho (STY) sites” was uploaded into Perseus 1.6.1.1 software for statistical analysis and filtering (Tyanova et al., 2016). P-sites that contained a contaminant, reverse match, 4

or had a location probability less than 0.75 were removed. Intensities were transformed into log2 values and valid values were assessed. With 6 runs, we required at least 5 valid values to be present in one of the groups (control samples or deletion mutant samples). These 1,072 sites were reduced to 661 by removing occurrences where 2, 3, or 4 valid values appeared in the other group to remove sites with insufficient data. A student’s t-test was performed on the two groups and sites with q-value less than 0.05 were considered significant (here 204). PCA plot was constructed with all mass spectrometry runs where the control strain clustered together as did the deletion mutant (Supplemental Figure 1). Differentially phosphorylated sites were analyzed by NetworKIN to predict which kinases target specific phosphorylation sites. Phosphosite-Kinase interactions with a score greater than 2 are considered significant (Horn et al., 2014). Following NetworKIN, Motif-X software was used to identify statistically enriched motifs (Schwartz and Gygi, 2005). The parameters were based on the following criteria: occurrence in at least 15 peptides, width of 13, significance level of 0.001. 2.5 RNAseq and Statistical Analysis Samples for transcriptomic data were grown identically as phosphoproteomic samples. Two biological replicates of harvested mycelia were immediately frozen, crushed, and prepped for RNA-seq analysis. For RNA-Seq analysis, sequencing libraries were constructed from RNA samples using TruSeq RNA Sample Preparation Kit v2 (Illumina, Inc. San Diego, CA) and 100bp reads were generated on the Illumina Genome Analyzer IIx platform (Illumina, Inc. San Diego, CA) at the Genomics Core Facility of the University of Nebraska Medical Center. RNASeq output data was checked for base quality and aligned to the reference genome of Aspergillus nidulans (www.aspgd.org/) using bowtie2 and the read counts were normalized using HT-Seq. Differential expression analysis was done using DESeq software (Anders and Huber, 2010). Genes were called differentially expressed based on log2fold change and significance is estimated for p-value less than 0.01. 2.6 Quantitative PCR analysis RNA purification was carried out using a QIAGEN RNeasy Plus Universal Mini Kit following the included protocol. Mycelia were lysed using a mortar and pestle cooled with liquid nitrogen. The RNA yield was quantified using a Thermo Scientific NanoDrop Lite. The A260/A280 ratio was used to assess purity. If ratio was not ~2.0 samples were digested using the QIAGEN RNase-Free DNase Kit. 10uL RDD buffer, 2.5uL DNase I stock solution and RNase free water (100uL total volume) were incubated 5 minutes at room temperature, then re-purified using the QIAGEN RNeasy kit. The purified RNA was then converted to cDNA using the Applied Biosystems High Capacity cDNA Reverse Transcription Kit and protocol. The forward and reverse primers for the target genes were designed using Primer3 (Untergasser et al., 2012). Product size was set to 150-300 base pairs and the primer melting point to 59˚C. The primers were obtained from Invitrogen (primer sequences available in Supplemental File, S1).The Reverse Transcriptase PCR reaction was run using a BioRad C1000 Touch Thermal Cycler with CFX96Real-Time System. The Applied Biosystems SYBR Green PCR Master Mix

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and protocol was used. Each reaction was run with 3 biological replicates and 3 technical replicates. The ∆∆Ct method was used for the data analysis (Livak and Schmittgen, 2001). 2.7 Fungal size analysis Fungi were grown in shake flasks as described above. A growth curve was constructed by measuring dry cell weight every 4 to 6 hours. During growth, samples (~5mL each) were removed from flasks and the average size of fungal elements was measured using a Mastersizer 3000 instrument with a Hydro SM manual sample dispersion unit (Malvern Instruments Ltd., Worcestershire, UK) (Quintanilla et al., 2017). Briefly, 1 mL sample was dispersed in tap water at a stirring speed of 1,800 rpm. The refractive index was set to 1.33 and a laser saturation of at least 1% was used to ensure a stable reading. At least two technical replicates were taken for each sample. Mastersizer 3000 software calculated a volume-weighted particle size distribution and the 90th percentile value, S90, was used to characterize morphological size (Quintanilla et al., 2017). A portion of the sample used for size analysis (0.5 mL) was mixed 1:1 with fixative solution (3.5% formaldehyde, 50mM phosphate buffer (pH 7.0), and 0.2% Triton X-100 (Harris et al., 1994) and stored at 4⁰ C. Fixed samples were viewed under a CarlZeiss Axiovert 200 microscope. 2.8 Coverslip analysis of growth and branching rate Coverslip experiments were used to assess specific growth and branching rates of the control strain and mpkA deletion mutant in a shear free environment. Briefly, coverslips were sterilized then incubated in concanavalin A solution (20mL of PBS, 100µL 132mM CaCl2, and 10.7mg Concanavalin A). After 20 minutes, coverslips were left to dry for an hour at 37⁰ C. Spores were harvested from MAGV plates and one milliliter of 1x105 spores/mL was dispensed onto each coverslip. After an hour at 28⁰ C, coverslips were submerged in YGV media in a petri dish and left for 8h. At hour 8, and each following hour, a fresh coverslip was placed onto a slide and 30 images of individual fungal mycelia were captured (CarlZeiss Axiovert 200 microscope with AmScope MU300 3.0MP Microscope Digital Camera). Images were analyzed (ImageJ 1.46r; (Schneider et al., 2012)) to quantify projected area and the number of branches for each mycelium, to determine an average projected area (A) and average number of tips (n) for each coverslip. In the presence of unlimited nutrients, total fungal hyphal length and number of tips increase exponentially (Trinci et al., 1994). As a result, specific growth rate can be defined in terms of mycelial projected area (Spohr et al., 1998) such that µA=ln (A/Ao) t (1) Where A is specific growth rate based on projected area (h-1), Ao is projected area (µm2) at time (t) zero and A is projected area (µm2) at subsequent times. Because after an initial period of time branching also occurs exponentially (Trinci et al., 1994), specific branching rate can be defined in terms of number of hyphal tips (Spohr et al., 1998) such that: kb=ln (n/no) t (2) Where kb is the specific branching rate (h-1), no is number of hyphal tips at time (t) zero and n is the number of tips at subsequent times. 2.9 Iron Studies 6

2.9.1 Iron replete and deplete growth Harvested spores (1x107) were inoculated into 250mL baffled flasks with 50mL of low pH minimal media (MM) (0.5% casamino acids, 1.0 % glucose, 1000ppm Hutner’s trace elements, and 1000 ppm vitamin mix, pH adjusted to 3.3). After 16 hours at 28⁰ C and 250rpm, the culture was added to 2.8L Fernbach flasks containing 1.2L of MM (pH 6.5) grown at 28⁰ C and 250rpm. For iron free culture, flasks were filled with acid (2M HCl) for 24 hours and iron free Hutner’s solution was used in the media (Hutner’s without FeSO4). Growth curves were produced by measuring dry cell weight every six hour until stationary phase. The growth rate was determined over the exponential growth phase. 2.9.2 Western Blotting Control strain A. nidulans was grown in three growth conditions, rich (YGV), +Fe (MM), and – Fe (MM with iron free Hutner’s). All conditions began with 1x10 7 spores inoculated into 50mL low pH YGV. Seed flasks grew for 12hours, where they then were used to inoculate 1.2L of the three different growth media. After 24 and 27 hours of growth, the YGV flask and +Fe (MM) flask, respectively, were harvested, frozen with liquid nitrogen, and prepared for western blot analysis. For the –Fe flask, 10μM FeSO4 was added and after 5, 30, and 60 minutes exposure, about 50mL culture was removed, biomass harvested, and frozen. Frozen mycelia were crushed with mortar and protein was extracted with approximately 1:1 (v/v) ratio of crushed cells to RIPA buffer (Thermo Fisher Scientific). 100 µg of protein was exposed to SDS-page electrophoresis and transferred to a nitrocellulose membrane (Life technologies, Carlsbad, CA). The membrane was blocked with 5% BSA for 1 hour at room temperature, followed by 1:2000 rabbit anti-phospho-p44/p42 MAPK antibody (#4370 Cell Signaling, Danvers, MA) overnight at 4⁰ C. After washing with TBS-T, anti-rabbit HRP-linked antibody (#7074 Cell Signaling, Danvers, MA) at 1:2000 in TBS-T was incubated with the membrane for 1 hour at room temperature. Bands were imaged following SuperSignal™ West Pico Chemiluminescent Kit (Pierce, Rockford, IL) manufacturer’s instructions. After imaging, membranes were washed 4 times with TBS-T and stripped with 8mL Restore™ PLUS Western Blot Stripping Buffer (Thermo Fisher Scientific) at 37⁰ C with slight agitation for 15 minutes. After four 5 minute washes with TBS-T, the membrane was incubated in blocking buffer for 1 hour at room temperature. 1:2000 mouse anti-p44/p42 MAPK antibody (#4696 Cell Signaling, Danvers, MA) was added to blocking buffer followed by 3 TBS-T washes. The membrane was exposed to 1:200 anti-mouse antibody (#7076 Cell Signaling, Danvers, MA) for 1 hour and was then processed for imaging. Quantification of western bands was performed using myImageAnalysis Software developed by Thermo Fisher Scientific. 2.9.3 Siderophore Assay Baffled 250mL flasks were filled with 2M HCl for 24 hours to remove any residual iron. Flasks were rinsed with DI water, filled with 50mL of minimal media (+/- Fe) and 1x107 spores, and grown at 28⁰ C and 250rpm. After 26 hours of growth the entire flask was vacuum filtered. The dry biomass was measured and approximately 1mL of the broth was saved. Broth was analyzed following the chrome azurol S (CAS) assay procedure developed by Schwyn and Neilands (Schwyn and Neilands, 1987). Briefly, 100µL broth was added to 100µL CAS shuttle solution in a 96 well plate and after approximately 10 minutes (or equilibrium), the absorbance was 7

measured at 630nm. Percent siderophore production was calculated according to Gupta et al., 2012 where the difference between Asample, the absorbance of the sample (CAS solution + broth from flask), and Aref, the absorbance of the reference (CAS solution + uninoculated media), is divided by Aref and multiplied by 100 (Gupta et al., 2012). The production value was divided by the flask biomass to account for differences in cellular mass. 2.10 Data Availability All strains in this work can be obtained through the Fungal Genetics Stock Center (FGSC) (Manhattan, KS, USA). RNA-seq data has been submitted to the NCBI Gene Expression omnibus, accession number GSE108325. Processed transcriptomics data can be found in Supplemental File, S2 and differentially phosphorylated sites can be found in Supplemental File, S3. 3. Results and discussion MpkA is a protein kinase involved in the fungal CWIS pathway (Fujioka et al., 2007). While MpkA is known to regulate expression of cell wall repair genes during wall stress (Fujioka et al., 2007), we studied MpkA function outside of wall stress. To do this, a control strain and an mpkA deletion mutant were grown in rich media (YGV) for approximately 20 hours (i.e., midexponential growth phase) and samples were removed to conduct a combined phosphoproteomic and transcriptomic analysis. Protein digestion was carried out using the protease, trypsin. Both analyses were carried out on two biological replicates. Phosphoproteomic analysis involved three technical replicates for each biological replicate and a PCA plot (Supplemental Figure 1) shows control strain replicates cluster together as does the mutant strain. Transcriptomic analysis was conducted employing RNA-sequencing technology and phosphopeptide analysis was conducted employing label-free quantitative mass spectrometry. This overall approach allowed us to study the impact of MpkA in the absence of induced cell wall stress. 3.1 Broad inspection of –omic hits In order to comprehensively characterize MpkA impact during steady state growth the entirety of the –omic data was assessed. Phosphoproteomic analysis identified 1,072 phosphorylation sites (p-sites) from 555 proteins in the combined control and ΔmpkA datasets. Of these, 204 p-sites from 175 proteins (Supplemental Table, S3) were differentially phosphorylated between the two strains. These differentially phosphorylated sites were processed using Motif-X, NetworKIN, and GO analysis (Linding et al., 2008; Mi et al., 2017; Schwartz and Gygi, 2005). Motif-X identified seven significantly enriched motifs ([pSP], [RXXpS], [RXXSXXpS], [pSDXE], [RpS], [PpS], and [pTP]) (Figure 1A), NetworKIN is a tool that uses a database of consensus motifs to predict the kinase most likely to phosphorylate it. All the motifs from Figure 1A were matched with putative upstream kinases using NetworKIN (Figure 1B). Of the 204 p-site analyzed, 76 were connected with a total of 30 kinases (Figure 1B). This analysis showed Cka1 was likely to phosphorylate pSDXE motifs and PkcA and PkaB to phosphorylate RXXpS. We identified seven kinases (BckA (S719), CkiB (S426), CotA (T87), Ksg1 (S760), PkcB (S633), SchA (S316), SteC (S535)) and eight transcription factors (AhpA (S87), AN1254 (T221),

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AN2857 (S467, S468), AreB (T96), CrzA (S387), Hsf1 (S451), Nmy1 (S287), StuA (S421)) to be differentially phosphorylated in the absence of MpkA. A. nidulans has 10,988 open reading frames and our RNA-seq captured 6,415 significant genes with a p value less than 0.05. Restricting the number of differentially expressed genes even further, 2,796 were expressed with a fold change (ΔmpkA/Control) less than 0.5 or greater than 2.0. 1,001 of these were upregulated in ΔmpkA and 1,795 were downregulated (Supplemental Table, S2). To corroborate RNA-seq results, quantitative PCR was carried out on 9 cell-wall related genes (agsA, dfgA, amyA, bglR, gelA, agnE, AN0541, AN4367, and AN1310) in both the control and the deletion mutant (Supplemental File, S1). With the exception of bglR, all of the genes follow the same trend as our RNA-seq data suggesting it is reliable. Upon comparison of differentially phosphorylated and expressed gene, 43 peptides from 38 proteins were in common. Out of these 36 peptides have fold changes in the same direction and 7 in opposite directions (Supplemental Table, S3). Global analysis of differential protein phosphorylation and transcript levels implies MpkA is linked to a number of different cellular processes. Not only this, but which proteins/genes are MpkA targets. To confirm involvement with some of these processes, we conducted experiments to determine if MpkA impacts cell-wall morphology, branching regulation, and iron starvation. 3.2 Cell wall strength In our transcriptomic data set we observe 98 differentially expressed genes related to the primary components of the cell wall - glucan, chitin, and mannoprotein (Latge, 2007). Of these, 21 were upregulated and 77 were downregulated (Table 1). Thirty of these differentially expressed genes have been previously identified as cell wall related genes in A. nidulans (de Groot et al., 2009). Although all the genes in Table 1 are over or under expressed in ΔmpkA by at least 2 fold, 25 of these experienced a greater than 10 fold change (denoted with asterisk in Table 1). Interestingly, all of the genes that showed large changes in expression were downregulated in the deletion mutant. Phosphoproteomic data revealed 3 cell wall related proteins that experienced significant phosphorylation differences, AN8710/chs5 (S283, putative chitin biosynthesis protein), AN4897 (S245, putative cell wall protein), and AN1015 (S11, alpha-1,4-glucan phosphorylase) (Wortman et al., 2009). One should note AN1015 was also transcriptionally downregulated 4 fold in the deletion mutant. 3.2.1 Expression of cell-wall related genes Our data show that even in the absence of wall stress, numerous wall-related genes show significantly reduced expression levels in an mpkA deletion mutant (Table 1). These include genes involved with: (i) synthesis of wall polymer precursors, (ii) biosynthesis of wall polymers themselves, and (iii) wall polymer connections. This implies MpkA is involved, either directly or indirectly, in regulation of expression of these wall-related genes, even during normal growth. We note that these numerous down-regulated genes are involved, at various levels, with cell wall biosynthesis. For example, wall polymers glucan and chitin are synthesized from uridine 9

diphosphate (UDP) sugars which are essential to the creation of the cell wall (Gow et al., 2017). Our data show fourteen UDP-processing genes to be downregulated in the mpkA deletion mutant. Of these, eight experienced a 5-fold or greater decrease (AN1310, AN4363, AN10392, AN5550, AN5846, AN12267, AN2574, AN10388). Not only were precursor synthesis genes downregulated, but also genes involved in biosynthesis of wall polymers themselves. For example, two synthase genes, agsA (catalytic subunit of 1,3-α-glucan synthase complex) and chsF (putative class III chitin synthase), were downregulated by 3.7 and 6.7 fold, respectively as well as 9 mannan processing genes. Once synthesized, wall polymers are covalently linked to form a strong, interconnected network. Transglycosidases are hypothesized to make connections between 1,3-β-glucan and the existing glucan network (de Groot et al., 2009). Our data show several transglycosidases (gelA, gelD, crhD, crhC) with reduced expression in the mpkA deletion mutant. Glucanases and chitinases can function as wall remodeling enzymes as well (Gow et al., 2017). The glucanases, agnE, agnC, mutA, AN3883, and AN0245, were all significantly downregulated, as were chitinases, AN0541, AN11059, and AN10838. Maintaining a balance of chitinase and glucanase enzymatic activity provides appropriate wall elasticity to allow for new growth, branching, and wall strength to prevent cell lysis (Bowman and Free, 2006). Taken together, the lack of precursor material, synthase genes, and polymer connectors likely impact cell wall morphology and strength. 3.2.2 Increased hyphal fragmentation during flask growth To determine whether reduced expression of a significant number of cell-wall-related genes in the mpkA strain impacts wall function, we conducted a simple experiment to indirectly evaluate hyphal tensile strength. Both control and deletion strains were grown in shake flasks on rich growth medium. There was no significant difference in specific growth rate (µ = 0.20 h-1) between the two strains (P = 0.11, Figure 2a) suggesting no growth impairments or cell lysing of the mutant. And while total biomass was similar over the duration of cellular growth, mycelial size was drastically different. Laser diffraction was used to measure the size distribution (equivalent spherical diameter) of fungal elements during growth (S90, m) (Quintanilla et al., 2017). The average size of the control strain was just over 2000 m, while the mpkA deletion mutant was significantly smaller (P < 10-40 ) at approximately 500 μm (Figure 2b). Because of the way laser diffraction measures size, and the fact that total biomass was similar in both strains, this size discrepancy could be due to either: (i) increased fragmentation of the deletion strain during flask growth such that each fungal element was smaller or (ii) a significant increase in branching of the deletion mutant, such that elements were comparable in mass to the control strain, but much smaller in size. Images of shake flask culture for the control (Figure 2C) and the mpkA deletion mutant (Figure 2D), from a number of time points, were inspected. Here six representative fragments (or fungal elements) of each strain clearly shows the size difference between the deletion strain and the control strain, with no readily observable difference in branching. This implies the observed size discrepancy is due to hyphal fragmentation of the mpkA deletion mutant during flask growth. And these increased levels of hyphal fragmentation imply the mpkA deletion mutant has a weaker cell wall than that of the control strain (Quintanilla et al., 2017). It is also somewhat surprising that while the mpkA deletion yielded hyphae more likely to fragment during flask growth, this increased level of hyphal fragmentation did not have a detrimental impact on the specific growth rate of the strain. 10

3.3 Branching regulation Filamentous fungi grow by extension of highly polarized, tubular hyphae. When nutrients are abundant, hyphae typically branch more frequently, effectively permitting growth while allowing hyphae to remain in the vicinity of the localized, nutrient rich environment (Carlile, 1995). Branching is a complicated coordinated cellular process that can be influenced by many factors ((Harris, 2008). From our phosphoproteomic data set, several putative branching related proteins were found to have altered phosphorylation status. 3.3.1 Altered Phosphorylation in proteins with putative role in branching regulation. CotA is a serine/threonine kinase with established function in maintaining cell polarity (Shi et al., 2008). In the mpkA deletion mutant, CotA was not phosphorylated at T87 (Table 2). NetworKIN predicted that the yeast kinase, STE20, phosphorylates this residue. The A. nidulans orthologue, Ste20, is a PAK (p21-activated kinase), predicted to be involved in hyphal morphogenesis and development (De Souza et al., 2013; Harris et al., 2009). Another protein, LagA was differentially phosphorylated in the mpkA deletion mutant. In particular, LagA was not phosphorylated at S30. LagA is involved in sphingolipid biosynthesis and its absence results in morphological defects, specifically hyphae are significantly distorted with multiple apical branches (Li et al., 2006). Another study in A. nidulans found that inhibition of sphingolipid biosynthesis caused decreased hyphal tip growth and branching increased (Cheng et al., 2001). Finally, Cdc24 is differentially phosphorylated in the mpkA deletion mutant, losing a phosphorylation at S627. Cdc24 (AN5592) is a guanine nucleotide exchange factor (GEF) (Si et al., 2016; Wendland and Philippsen, 2000) which localizes to hyphal tips and is required for polarity establishment (Si et al., 2016). In A. fumigatus MpkA and the CWIS pathway activation is required for normal polar extension of hyphae during accelerated growth (Dirr et al., 2010). These three known branching regulators all experienced a change in protein phosphorylation which may impact protein activity causing an mpkA deletion aberrant branching phenotype. 3.3.2 Increased branching rate in a shear free environment Specific branching rate (kbranch h-1) was used as a metric to quantitatively assess aberrant branching phenotypes. For this assessment, fungi must be grown in an environment absent of shear stresses which could fragment weak hyphae (Pollack et al., 2008). To do this, we grew fungi fixed to coverslips in quiescent growth medium. Under these conditions, we quantified fungal morphology using microscopy and digital image analysis. We found no statistically significant difference in specific growth rate between the control and the deletion mutant (P > 0.05, data not shown). In contrast, we found the mpkA deletion mutant had a statistically significant (P < 0.01) higher specific branching rate (0.28 h-1) than the control strain (0.21 h-1, Figure 3A&B). Representative images from this experiment (Figure 3C) confirm that after 15 hours of growth, the deletion mutant has more branches than the control strain. These results support our –omic findings linking MpkA to branching. 3.4 Iron starvation response

11

While iron is a crucial element, acting as a cofactor for many enzymes and as an electron carrier in the electron transport systems (Schaible and Kaufmann, 2004), an overabundance of iron can be toxic (Hortschansky et al., 2007). This implies maintenance of iron homeostasis is a critical cell function. In A. fumigatus, MpkA is thought to assist in iron homeostasis by regulating siderophore biosynthesis (Jain et al., 2011), namely triacetylfusarinine C (TAFC) and ferricrocin (FC) (Eisendle et al., 2006). Similarly, in Fusarium oxysporum, FoSlt2 (MpkA homologue) was required for siderophore biosynthesis (Ding et al., 2015). Cell wall integrity pathway has been connected to iron homeostasis in a variety of fungal species such as Cryptoccus neoformns (Jung et al., 2006), Candida albicans (Bai et al., 2006), Metarhizium rileyi (Song et al., 2016), and Colletotrichum graminicola (Albarouki and Deising, 2013). In our RNA-seq experiment we identified over 25 iron related genes whose expression level changed in the deletion mutant (Table 2). To ensure that MpkA is involved, several experiments were conducted in iron replete and deplete conditions, described below. 3.4.1 Global –omics analysis identifies known, iron-related genes and proteins Genes involved with iron metabolism and the response to iron starvation fall into several functional categories including: (1) ornithine (siderophore precursor) biosynthesis and transport (Dzikowska et al., 1999), (2) siderophore biosynthesis (Oberegger et al., 2002), (3) siderophore transport (Haas, 2003), and (4) transcriptional regulation of iron homeostasis (Hortschansky et al., 2007). In each of these categories, we find informative examples of differential gene expression or protein phosphorylation. We note that phosphoproteomic and transcriptomic experiments were carried out on fungi grown in rich medium. Thus, results reported here provide insight regarding MpkA function when iron is replete. Ornithine Biosynthesis and Transport Genes: Ornithine (C5H22N2O2) is the precursor molecule for both TAFC and FC (Figure 4). Several of these genes include: ornD (acetylglutamate synthetase; AN5867), amcA (ornithine transporter; AN8881), agaA (arginase; AN2901), and argB (ornithine transcarbomyl; AN4409) and all were downregulated. In addition to reduced levels of agaA transcript, AgaA was not phosphorylated on S88 in the mpkA deletion mutant (Table 2). These changes in ornithine biosynthesis and transport genes suggest that overall cellular levels of ornithine may be lower in the mpkA deletion strain as was observed in ΔmpkA A. fumigatus (Jain et al., 2011). Siderophore Biosynthesis Genes: Siderophores are synthesized by a series of reactions that convert ornithine into the two distinct molecules, TAFC and FC (Figure 4). Transcriptomics reveal that sidA (L-ornitihine N5-monooxygenase; AN5823) expression was 4.5 times higher, but without sufficient raw material (i.e., ornithine) this will not increase siderophore biosynthesis. However, sidC (non-ribosomal peptide; AN0758) and sidL (N5-hydroxyornithine-acetylase; AN10080), both essential for FC biosynthesis (Blatzer et al., 2011), expression levels decreased with a fold change of 0.46 and 0.4, respectively. Inactivation of SidL , in A. fumigatus, resulted in decreased FC biosynthesis during iron starvation (Blatzer et al., 2011). Siderophore Transport Genes: Extracellular iron is carried across the cell membrane by TAFC molecules making siderophore transport extremely important for supplying iron to the cell. Three known transmembrane siderophore transporter proteins, MirA, MirB, and MirC, (Haas, 2003) 12

were all identified in the –omic sets (Figure 4). From phosphoproteomic data MirB was not phosphorylated in the control at S55 (Table 2) and RNA-sequencing showed MirA and MirC were transcriptionally downregulated in ΔmpkA by 3 fold each, while MirB was upregulated by 4 fold. Three putative siderophore transporters, AN5378, AN3763, and AN8365, all showed increased expression (2.0, 3.1, and 4.2-fold, respectively) in our ΔmpkA strain. AN3763 was also over phosphorylated at S36 suggesting that MpkA regulates this transporter both transcriptionally and post-transcriptionally. Transcriptional Regulation of Iron Homeostasis Genes: HapB is a member of the well-known CCAAT-binding complex (CBC) (Hortschansky et al., 2007) and our data shows its transcript level is 2 fold lower than those in the control strain. Additionally, CpcA, a transcriptional activator involved in cross-pathway control-mediation of amino acid biosynthesis, was downregulated with a fold change of 0.40. A recent study by Beckmann et al., found CpcA deficient A. fumigatus strain had a 45% decrease in ornithine content (Beckmann et al., 2013). Thus, reduced cpcA expression may lead to reduced ornithine levels in ΔmpkA. Many of the proteins described in the siderophore biosynthesis and transport pathway were found in the transcriptomic dataset to be downregulated. We hypothesize, as in A. fumigatus, MpkA is acting in a manner that regulates ornithine content, which in turn impacts iron homeostasis. 3.4.2 MpkA phosphorylated in response to Fe levels resulting in increased siderophore expression. To verify MpkA functionality on iron starvation, a control strain was grown in liquid culture under an iron deplete condition. After 24 hours growth, iron was added to the growth medium (to a final concentration of 10μM) and mycelia were harvested after 5, 30, and 60 minutes. Cell lysates were subjected to western blot analysis to determine MpkA phosphorylation levels. Figure 5 shows MpkA is phosphorylated at low levels during all three steady state conditions (i.e., growth in “YGV”: rich medium for 24 hours; “0 min”: minimal medium lacking iron for 24hours; “+Fe”: minimal medium containing iron for 24 hours). However, immediately after iron addition, MpkA becomes increasingly phosphorylated. The dramatic change in phosphorylation of MpkA due to a disturbance in iron homeostasis suggests MpkA plays a role in iron regulation. Not only does the phosphorylation status of MpkA change, but the growth rate is impacted during iron starvation. When a control strain is grown in Fe- conditions there is a significant decrease in specific growth rate compared to Fe+ conditions, going from 0.183 to 0.156 hr-1 (P < 0.05). However, when the mpkA deletion mutant is grown in Fe+ or Fe- conditions there is no significant change in specific growth rate (0.21 and 0.22 hr-1). This implies that in the absence of mpkA, A. nidulans is unable to correctly reduce growth rate in response to limited iron availability. This finding is consistent with observations made in a siderophore production assay (Figure 6), where the control strain secretes a significantly higher amount of siderophores during Fe- growth than during Fe+ growth. In contrast, the mpkA deletion mutant produces the same, low level of siderophores, regardless of the presence or absence of iron. This suggests MpkA

13

plays an important role in siderophore expression when the availability of exogenous iron becomes limiting. 3.5 Other putative cellular roles of MpkA In addition to the cellular processes mentioned above, our data imply other processes in which MpkA is likely involved. These include reactive oxygen species, autophagy, and polyketide synthesis. 3.5.1 Reactive Oxygen Species: Transcriptomic data revealed seven NADPH oxidase (NOX)/Reactive oxygen species (ROS) genes were significantly under expressed in ΔmpkA. In A. nidulans, NADPH oxidase (Nox) is responsible for the generation of ROS at hyphal tips and this accumulation plays a large role in enforcing apical dominance (Semighini and Harris, 2008). NoxR, the regulatory subunit of NOX, activates NOX to generate the ROS signal (Fleissner and Herzog, 2016) and here, NoxR homologue, AN6046, was expressed 10 fold less in the mpkA deletion mutant. In Neurospora crassa, the ROS signal is mediated by HAM-6, HAM-7, and HAM-8 sensing on the cell wall (Fu et al., 2014). A. nidulans homologues of these, AN5458, AN4702, AN4264, were all significantly under expressed in the mpkA deletion mutant. In Podospora anserina, IDC-1, IDC2, and IDC-3 (Impaired in the Development of Crippled Growth) were connected with PaMpk1 (homologue of A. nidulans MpkA) in regulating CAT (Lalucque et al., 2017; Tong et al., 2014). IDC-1, IDC-2, and IDC-3 homologues in A. nidulans (AN2071, AN7322, and AN3606) also experienced a decrease in expression (0.10, 0.48, and 0.17, respectively) in the deletion mutant. Moreover, in A. fumigatus, studies with ΔmpkA revealed increased sensitivity to reactive oxygen species diamide and menadione (Valiante et al., 2008). Here we present evidence of MpkA in A. nidulans impacting HAM, IDC, and Nox proteins which are involved in hyphal branching and fusion. This occurs in the absence of cell wall damage, and could account for MpkA role in morphogenesis and development. We hypothesize that NoxR activates NOX to generate the ROS signal which is relayed to MpkA via HAM/IDC homologues. This results in MpkA activation that enhances NoxR/IDC/HAM expression as a positive feedback loop. 3.5.2 Autophagy Autophagy is the cellular process responsible for non-specific degradation and recycling of cellular components which is induced under starvation conditions (Pollack et al., 2009). Atg13 is an autophagy protein showing increased phosphorylation at S350 in ΔmpkA. When Atg13 becomes phosphorylated it does not associate with other autophagy complex proteins (such as Atg1), meaning autophagy is turned off (Kamada et al., 2000). Several other putative autophagy proteins changed phosphorylation state as well, including: Atg18 (S283), Atg26 (S619), and Sec16 (S419) (all down phosphorylated in ΔmpkA) (Table 2) (Gimeno et al., 1996; Nitsche et al., 2012; Pollack et al., 2009). Autophagy has been linked to fungal morphology, where defects in autophagy genes showed delayed germination, reduced numbers of aerial hyphae, and disrupted conidiation (Pollack et al., 2009). Fusarium graminearum autophagy protein, FgAtg9, is required for normal vegetative hyphal morphology (Zheng et al., 2018). In A. nidulans, cell walls of 14

mycelia treated with rapamycin (leading to induction of autophagy), became weaker due to cellular degradation of cell wall components to provide a carbon source (Kim et al., 2011). Moreover, a connection between MpkA homologue, Mps1, in Magnaporthe oryzae with autophagy pathway is known to aid in cell penetration and pathogenicity (Liu et al., 2012). S. cerevisiae MpkA homologue SLT2 is required for mitophagy and pexophagy (degradation of mitochondria and peroxisomes, respectively) (Mao et al., 2011). 3.5.3 Polyketide synthesis Secondary metabolites are natural products of fungi with various biological activities that have been found very beneficial for the medical industry (Yaegashi et al., 2013). In our transcriptomic dataset we observed 22 polyketide synthases and NRPS (or NRPS-like) genes that were differentially expressed. A full list of these can be found in Supplemental File, S4. Of particular interest is PkfA (AN3230), a required polyketide synthase for aspernidine A synthesis (Yaegashi et al., 2013). Yaegashi et al., discovered that mpkA regulates aspermidine A synthesis (Yaegashi et al., 2013). We found that in the mpkA deletion mutant pkfA is downregulated almost 300 fold and not phosphorylated at S1758 (Table 2). Moreover, in the deletion mutant SteC is not phosphorylated at S535. SteC is a MAPK member of the SteD-SteC-MkkB-MpkB signaling module known to control sexual development and secondary metabolism (Bayram et al., 2012). This change in phosphorylation of SteC and the change in expression of 22 secondary metabolism genes from an mpkA deletion suggests, MpkA plays a role in secondary metabolism regulation. Many secondary metabolites have been found to be regulated by MpkA homologues in a variety of species (Valiante, 2017). For example, A. fumigatus secondary metabolite expression was differentially enriched in a ΔmpkA strain transcriptomic study (Altwasser et al., 2015) and in both Cochliobolis heterostrophus and Alternaria alternata, secondary metabolite, melanin, production depended on MpkA orthologue, Mps1 and AaSLT2, respectively (Eliahu et al., 2007; Yago et al., 2011). These studies strengthen our hypothesis of MpkA activity in secondary metabolism in A. nidulans. 4. Conclusion MpkA is an important signaling protein known to have a major role in the CWIS pathway. Beyond this, MpkA plays roles in cellular processes outside of this pathway in the filamentous fungi A. fumigatus, N. crassa, P. anserina, C. heterostrophus, and A, alternata. We have found the same is true in A. nidulans. MpkA is connected with iron homeostasis, branching, and cell morphology. Fungi with an mpkA deletion had weaker cell walls, a higher branching rate, and were unresponsive to changes in exogenous iron. Moreover our –omic sets revealed possible connections to reactive oxygen signaling, autophagy, and polyketide synthesis. Combined phosphoproteomic and transcriptomic analysis offer global insight into MpkA function. Both datasets are available for researchers to continue hypothesis testing and validation studies. Acknowledgements This work was supported by the National Science Foundation (Awards 1517309, 1517133, and 151690). The UNMC DNA Sequencing Core Facility receives partial support from the Nebraska Research Network In Functional Genomics NE-INBRE P20GM103427-14, The Molecular Biology of Neurosensory Systems CoBRE P30GM110768, The Fred & Pamela Buffett Cancer 15

Center - P30CA036727, The Center for Root and Rhizobiome Innovation (CRRI) 36-5150-208520, and the Nebraska Research Initiative.

16

Table 1: RNA-seq differentially expressed cell wall related genes. Upregulated genes have a fold change (ΔmpkA/control) >2 and downregulated genes have a fold change of <0.5. Category

Function Glucosidase

Proteins involved in glucan synthesis and processing

Proteins involved in mannan synthesis and processing

Proteins involved in chitin synthesis and processing

Upregulated Genes

Downregulated Genes

bglH, AN4825

bglR*, bglJ*, bglO*, bglA*, bglG, bglB, agdA, agdE, AN0280

Glycosidase

aglE*

Galactosidase

aglF

Glucuronidase

AN3200*, AN2395

Transglycosidase

gelA, gelD, crhD, crhC

Glucanase

agnD, btgC

agnE*, agnC, mutA, AN3883, AN0245

Endoglucanase

AN1602, AN2388, AN5214

AN6786*, AN8068, eglB, eglD

Cellulose synthase involved in glucan synthesis

celA

Cellobiosidase or cellulase involved in degredation of glucans Glucan synthase

cbhA, cbhB

Endo-mannase

dfgA*, dfgD, manA

Mannosyltransferase

AN1969, AN7562

Cell wall mannoprotein

mnpA*

Mannosidase Galactosidase involved in degradation of mannans Chitinase

mndC

agsA

aglC*, aglG AN0549

AN1852, AN4823, AN9380

Chitosanase

AN11051

Chitin Synthase

AN4367

Other

nagA AN1310*, AN4363*, AN10392*, AN5550, AN5846, AN12267, AN2574, AN10388, AN3351, AN4792, AN7075, AN1142, AN3083, AN2387

UDP-N-acetylmuramate dehydrogenase activity UDP Processing

AN11981, AN2648 UDP-N-acetylglucosaminedolichyl-phosphate Nacetylglucosaminephosphotra nsferase activity Putative cell wall macromolecule catabolic process

Other cell wall related

AN0541*, AN11059*, AN10838

Chitin deacetylase

Cell wall localization

AN5888

AN6405, AN10104, AN0511 AN11979, AN11411, AN4494, AN0570, AN4594, AN11419, AN2928

Hydrophobin Amylase

AN0542*, AN0543*, AN8969*, AN5076, AN4644, AN9389 AN7269*, AN9345*, AN7274, AN5258, AN3212 AN6401*, AN7539*, AN1837*, rodA

amyG

amyA*

* fold change greater than 10 Bold = gene with known cell wall related function and presence in de Groot et al., 2009 or Fujioka et al., 2007 cell wall study 17

Table 2: Proteins of various cellular processes with phosphorylation differences in ΔmpkA. Gene Name

P-site

+/- in ΔmpkA

Peptide Sequence

P value

Andromeda Score

1.5E-16 5.4E-04 5.5E-04 5.0E-03

102.9 100.9 119.5 147.5

Shi et al., 2008 Li et al., 2006 Si et al., 2016 Si et al., 2016

5.4E-04 1.6E-02 1.6E-02

122.7 101.0 66.6

Haas et al., 2012 Haas, 2003 Haas et al., 2008

5.4E-04 1.9E-19

97.7 125.0

Yaegashi et al., 2013 Bayram et al., 2012

3.1E-02 1.9E-03 2.4E-04 2.5E-03

88.11 112.34 129.75 212.55

Pollack et al., 2009 Pollack et al., 2009 Nitsche et al., 2012 Gimeno et al., 1996

Reference

Branching AN5529 (cotA) AN2464 (lagA) AN5592 (cdc24) AN5592 (cdc24)

T87 S30 S627 S764

-

pTAGNTAPGQQQQPGHLAPPVPR GDTSAPAMSTMNEVpSPIDPK NGNSYFpSPTESAR SQNNpSPTNQSLPIR

AN2901 (agaA) AN8540 (mirB) AN3763

S88 S55 S36

+ +

AVpSAVTETLSSQVYEHSK EVGINDNSpSDEALPSQHVQTGVQK VAPNSGpSDSDPSDLDLFTR

AN3230 (pkfA) AN2269 (steC)

S1758 S535

-

DEAEVLpSLAESDDTFLK DSIASSSLHPLQEEpSPVEPNRK

Iron Regulation

Polyketide Synthesis

Autophagy AN2076 (atg13) AN0127 (atg18) AN4601 (atg26)* AN6615 (sec16)*

S350 S283 S619 S419

-

VpTPEVGSAPLTR pSLSSLSQSPER DGPEMQYTNpSDSEQESK pSPENVQEPASEEDLAAR

*Denotes protein with putative function based on homology; p indicates phosphorylated residue in peptide

18

Table 3: Transcriptomic identifications differentially expressed associated with iron regulation. “FC”, Or fold change, indicates the number of reads in the deletion mutant over control. Gene

FC

qVal(FDR)

Putative Function

Transcriptional Regulation of Iron Homeostasis AN3675 cpcA 0.40 5.41E-36 Transcription factor of Gcn4p c-Jun-like family AN8251 hapX 1.78 1.57E-08 bZIP transcription factor AN7545 hapB 0.49 5.65E-09 Component of CCAAT-binding complex AN2621

acvA

AN2623 AN8777

aatA amdS

AN9339 AN6246 AN1604 AN0403 AN6237 AN2470

catB cycA

Known targets of CBC 0.46 0.0005 Delta-(L-alpha-aminoadipyl)-L-cysteinyl-D-valine synthetase 0.41 5.13E-11 Isopenicillin-N N-acyltransferase 0.50 0.0009 Acetamidase Known targets of SreA 2.54 3.29E-11 Hyphal catalase 1.93 1.14E-18 Cytochrome C 0.00 0.0164 Putative alpha-1,3-glucanase 3.75 2.59E-40 Ortholog(s) pyridine nucleotide-disulphide oxidoreductase 2.04 1.28E-14 Ortholog(s) ABC multidrug transporter 0.30 0.0302 Ortholog(s) alcohol dehydrogenase

Reference Beckmann et al., 2013 Hortchansky et al., 2007 Hortchansky et al., 2007 Bergh et al., 1996 Bergh et al., 1996 Littlejohn and Hynes, 1992 Oberegger et al., 2002 Hortchansky et al., 2007 Schrettl et al., 2008 Schrettl et al., 2008 Schrettl et al., 2008 Schrettl et al., 2008

Ornithine Biosynthesis and Transport Genes AN5867

ornD

0.40

8.40E-30

AN2901 AN8881

agaA amcA

0.13 0.67

1.76E-151 7.87E-07

AN4409 AN1810

argB otaA

0.37 0.12

3.60E-40 1.17E-163

Ortholog(s) have acetyl-CoA:L-glutamate Nacetyltransferase activity Arginase, hydrolysis of arginine to urea and ornithine Mitochondrial ornithine carrier protein Ornithine carbamoyltransferase Ornithine transaminase, involved in utilization of ornithine to produce proline

Schrettl et al., 2010 Haas et al., 2012 Oberegger et al., 2001, Schrettl et al., 2008 Upshall et al., 1986 Dzikowska et al., 1999

Siderophore Biosynthesis Genes AN5823 AN0758

sidA sidC

AN10080 sidL 0.41 8.17E-16 AN0609 sidI 2.30 1.13E-06 AN10764 2.33 0.0147 AN6239 2.61 9.67E-12 AN7884 48.27 2.88E-247 Siderophore Transport Genes

Ferricrocin (FC) biosynthetic transacetylase TAFC biosynthetic enoyl-CoA hydratase Ortholog(s) in N',N'',N'''-TAFC biosynthetic process Ortholog(s) siderophore biosynthesis lipase/esterase NRPS similar to FC peptide synthetases

Eisendle et al., 2003 Eisendle et al., 2003, Schrettl et al., 2008 Blatzer et al., 2011 Yasmin et al., 2011 AspGD, 2011 Schrettl et al., 2008 Andersen et al., 2012

AN7800 AN7485 AN0404 AN5378 AN8365 AN3763

Siderophore iron transporter Predicted siderophore iron transporter Ortholog(s) are ABC multidrug transporter Ortholog(s) have ferrichrome transporter activity Putative siderophore transporter Putative siderophore transporter

Haas et al., 2003 Haas et al., 2003 Oberegger et al., 2002 Haas et al., 2008 Haas et al., 2008 Haas et al., 2008

mirA mirC atrH

4.56 0.47

0.33 0.38 2.91 2.00 4.15 3.12

1.27E-79 0.0587

0.0008 8.29E-34 5.50E-08 7.72E-08 3.79E-55 2.50E-32

L-ornithine N5-monooxygenase Ortholog(s) Ferricrocin (FC) NRPS

19

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A.

B.

A.

B.

A.

B. Control ∆mpkA

*

Control ∆mpkA

C.

citrulline

HMG-CoA

arginine

citrulline ArgB

Hmg1

ornithine AmcA

AgaA

mevalonate SidI mevalonyl-CoA

ornithine

OrnD glutamate

mitochondrion

acetyl-CoA

SidA

SidH Anhydromevalonyl-CoA

N5-hydroxyornithine SidF

N5-anhydromevalonylN5-hydroxyornithine

acetyl-CoA

? NpgA

SidL

N5-acetylN5-hydroxyornithine glycine serine

SidD SidC

fusarinine C acetyl -CoA

FC

SidG Fe-TAFC TAFC

Differentially regulated in –omic data No change

MirC

MirA MirB Fe-TAFC

TAFC Fe

YGV Time after Fe addition +Fe 0m 5m 30m 60m PhosphoMpkA Total MpkA

*

Control

*

∆mpkA

Figure 1: Analysis of differentially phosphorylated sites between the control and mpkA deletion mutant. A: Motif-X analysis of the differentially phosphorylated peptides shows 7 significant phosphorylation motifs at p<0.01. B: NetworKIN software revealed 76 sites with a significant prediction score, of which Cka1 was predicted to phosphorylate 15 residues, followed by PkcA with 8 and Nrc2 with 7. Bar colors indicate the type of motif (from part A) that these 76 peptides contain. Here we connect the enriched motifs with kinases likely to phosphorylate them. Figure 2: Growth curve and particle size analysis from shake cultures reveal fragmentation of ΔmpkA. A: DCW measurements were taken for the control strain and the deletion mutant until stationary phase. The growth rate from 4 biological replicates of the control strain was found to be 0.22 hr -1 whereas the deletion mutant had a growth rate of 0.18 hr -1 (no significant difference). B: Control strain and ΔmpkA samples were analyzed on a Malvern 3000 instrument, and the 90th percentile (S90) from the size distribution was used for comparison. There was a significant size difference (p<0.01, n=4) between the strains suggesting that the mycelia of the deletion mutant are breaking in the flask from the shear forces. Images of six representative mycelium taken from shake cultures (C: Control at 21 hours growth & D: ΔmpkA at 20 hours growth) confirm that the size difference is a result of breaking and not highly compact/branched mycelium. Figure 3: Ideal growth conditions reveal MpkA role in branching. A: Control strain A. nidulans and mpkA deletion mutant were grown in YGV media on coverslips for 8 hours and every hour fungal morphology (here average number of tips) was assessed. B: Growth rates and branching rates were calculated during exponential growth. There was no significant difference in specific growth rate (control is 0.47 hr-1, ΔmpkA is 0.50 hr-1) however, the branching rate significantly increased in the deletion mutant (*indicates p < 0.01, n=3, error bars depict standard error). C: Representative images from coverslip experiment at 10 hours, 12 hours, and 15 hours after inoculation. Figure 4: Schematic of siderophore synthesis and transport in A. nidulans. Colored boxes (green - up, red - down) represent proteins that were differentially expressed or phosphorylated in either –omic set. Pathway adapted from Hortschansky et al., 2007 and Haas 2012. Figure 5: Western blot of MpkA phosphorylation in response to iron. The control strain (i.e., mpkA+) was grown in rich media (YGV), minimal media containing iron (+Fe), and minimal media without iron (-Fe). At 20 hours after inoculation, Fe was added to the -Fe culture. Time 0m is directly before adding FeSO4 to a final concentration of 10μM. Samples were harvested at 5, 30, and 60minutes after iron exposure. Data imply MpkA becomes transiently phosphorylated in response to iron addition. Figure 6: Siderophore production in response to iron availability. A. nidulans control strain and mpkA deletion mutant were grown in minimal media (+Fe) and minimal media lacking iron (-Fe). After 26 hours growth, Chrome Azurol S assay was conducted on broth, and fungal biomass was measured. There 25

is no significant difference in siderophore production in ΔmpkA in response to iron (i.e., +/-Fe) suggesting MpkA plays a role in siderophore regulation. The control strain significantly changes siderophore production in response to iron starvation. (* at p<0.01)

Supplemental Figure 1: PCA plot comparing phosphoproteomics runs. Six MS runs for the control strain (blue) and the mpkA deletion strain (red) show that strains cluster together.

26

Highlights:    

Phosphoproteomics and transcriptomics revealed the broad cellular role of MpkA An mpkA deletion mutant had weaker walls and a higher branching rate MpkA appears to play a role in iron metabolism Other connected pathways include ROS/NOX, autophagy, and polyketide synthesis

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