- Email: [email protected]
Uncovering the Serine Hydrolytic Landscape of Mycobacterium tuberculosis
Please cite this article as: Tonnus et al., ‘‘Death is my Heir’’—Ferroptosis Connects Cancer Pharmacogenomics and Ischemia-Reperfusion Injury, Cell Chemical Biology (2016), http://dx.doi.org/10.1016/j.chembiol.2016.02.002
Cell Chemical Biology
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including the disease-causing species M. avium and M. abscessus, which further expands the biological importance of these findings. Future work will likely focus on determining the roles of these giant lipids in mycobacterial membrane function. Other mycobacterial trehalose lipids confer resistance to membrane desiccation (Harland et al., 2008), but this property probably depends on hydrogenbonding free hydroxyls, which are absent in TPP. On the other hand, TPP contains numerous cis-unsaturations, which disrupt lipid chain packing and suggest that changes in TPP content might modulate membrane fluidity, perhaps in response to environmental cues. A possible role for TPP in disease could be tested through deletion of the newly identified TPP biosynthetic genes in a virulent species like M. avium, followed by experimental infection.
ACKNOWLEDGMENTS This work was supported by 1R21AI103321 to J.C.S. and U19 111224, R01 116604, and a Gates Foundation Vaccine Accelerator Award to D.B.M.
REFERENCES Asselineau, C., Montrozier, H., and Prome´, J.C. (1969). Eur. J. Biochem. 10, 580–584. Asselineau, C.P., Montrozier, H.L., Prome´, J.C., Savagnac, A.M., and Welby, M. (1972). Eur. J. Biochem. 28, 102–109. Burbaud, S., Laval, F., Lemassu, A., Daffe´, M., Guilhot, C., and Chalut, C. (2016). Cell Chem. Biol. 23, this issue, 278–289. Harland, C.W., Rabuka, D., Bertozzi, C.R., and Parthasarathy, R. (2008). Biophys. J. 94, 4718– 4724. Layre, E., and Moody, D.B. (2013). Biochimie 95, 109–115. Layre, E., Sweet, L., Hong, S., Madigan, C.A., Desjardins, D., Young, D.C., Cheng, T.Y., An-
nand, J.W., Kim, K., Shamputa, I.C., et al. (2011). Chem. Biol. 18, 1537–1549. Sartain, M.J., Dick, D.L., Rithner, C.D., Crick, D.C., and Belisle, J.T. (2011). J. Lipid Res. 52, 861–872. Seeliger, J.C., Holsclaw, C.M., Schelle, M.W., Botyanszki, Z., Gilmore, S.A., Tully, S.E., Niederweis, M., Cravatt, B.F., Leary, J.A., and Bertozzi, C.R. (2012). J. Biol. Chem. 287, 7990–8000. Sonde´n, B., Kocı´ncova´, D., Deshayes, C., Euphrasie, D., Rhayat, L., Laval, F., Frehel, C., Daffe´, M., Etienne, G., and Reyrat, J.M. (2005). Mol. Microbiol. 58, 426–440. Touchette, M.H., Holsclaw, C.M., Previti, M.L., Solomon, V.C., Leary, J.A., Bertozzi, C.R., and Seeliger, J.C. (2015). J. Bacteriol. 197, 201–210. Vats, A., Singh, A.K., Mukherjee, R., Chopra, T., Ravindran, M.S., Mohanty, D., Chatterji, D., Reyrat, J.M., and Gokhale, R.S. (2012). J. Biol. Chem. 287, 30677–30687. Yadav, G., Gokhale, R.S., and Mohanty, D. (2003). J. Mol. Biol. 328, 335–363.
Uncovering the Serine Hydrolytic Landscape of Mycobacterium tuberculosis Helena I. Boshoff1,* 1Tuberculosis Research Section, Laboratory of Clinical Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA *Correspondence: [email protected] http://dx.doi.org/10.1016/j.chembiol.2016.02.002
In this issue of Cell Chemical Biology, Ortega et al. (2016) present a study utilizing a click-chemistry-enabled fluorophosphonate for activity-based identification of serine hydrolases, pinpointing a range of proteins including previously annotated hypotheticals. The application of this technology on both actively replicating and non-replicating Mycobacterium tuberculosis gives us a glimpse of its serine hydrolytic landscape during different stages of metabolic activity. Despite 60 years of anti-tubercular therapy, tuberculosis afflicts almost 10 million people annually, with 1.5 million deaths in 2014 (World Health Organization, 2015). The average duration for the treatment of drug-sensitive tuberculosis is 6 months and consists of a backbone regimen of rifampicin, pyrazinamide, and isoniazid, with a fourth agent to prevent emergence of drug resistance. The problems in clinical management of such an extensive therapy and the toxicities associated with
current anti-tubercular drugs contribute to non-compliance, which in turn is associated with relapse and emergence of drug resistance. The pipeline of drugs in clinical or pre-clinical development is limited, and it remains to be seen what the sterilizing potential of these agents will be in tuberculosis patients. The development of drugs that inactivate essential processes in both replicating as well as non- or slowlyreplicating bacilli, could conceptually contribute to treatment shortening.
Most metabolic inhibitors are competitive, non-competitive, or uncompetitive inhibitors of an enzyme, with the extent of inhibition in vivo dependent on concentrations of their substrate. Thus, the challenge in target-based drug discovery efforts is the identification of chokepoints in metabolism, whose partial inhibition has a catastrophic effect on bacterial metabolism. Inhibitors that form covalent adducts in the enzyme active site, in contrast, irreversibly
Cell Chemical Biology 23, February 18, 2016 ª2016 Elsevier Ltd All rights reserved 209
Please cite this article as: Tonnus et al., ‘‘Death is my Heir’’—Ferroptosis Connects Cancer Pharmacogenomics and Ischemia-Reperfusion Injury, Cell Chemical Biology (2016), http://dx.doi.org/10.1016/j.chembiol.2016.02.002
Cell Chemical Biology
Previews
Figure 1. A Chemoproteomic Approach to Labeling and Identifying Growth-Phase Dependent Serine Hydrolases in M. tuberculosis This figure illustrates a chemoproteomic approach using a fluorophosphonate activity-based probe (FP ABP) to label and identify serine hydrolases in M. tuberculosis during different growth phases. The FP ABP probe only labels serine hydrolases with a catalytically active serine, hereby distinguishing expressed yet inert protein from active enzyme.
inactivate the enzyme and can achieve full inhibition of the metabolic process. There are several examples of drugs that covalently modify their target, with b-lactams being classical examples of activity-based covalent inhibitors. b-lactams rely on their mimicry of the N-acyl-D-alanyl-D-alanine peptidoglycan peptide stems to acylate the active site nucleophilic serine of the transpeptidases involved in bacterial peptidoglycan cross-linking (Tipper and Strominger, 1965). Despite the general concern of reactivity for drugs that are covalent modifiers, high selectivity can be designed during inhibitor development based on substrate specificity of the enzyme. Serine hydrolases including the classical D,D-transpeptidases, but also a number of other enzymes including viral proteases, acetylcholinesterase, serine proteases critical for blood clotting, and dipeptidyl peptidase 4 have successfully been targeted in drug development using activity-based suicide inhibitors (Bachovchin and Cravatt, 2012). Essential serine hydrolases in Mycobacterium tuberculosis, the etiologic agent of tuberculosis, could potentially serve as starting points for rational drug design. In support of this, the discovery of lassomycin, which kills both replicating and non-replicating M. tuberculosis by binding to the N-terminal domain of the ClpC1 complex, thereby stimulating ATPase hydrolysis uncoupled from proteolysis, has demonstrated the utility of targeting serine hydrolases such as the essential ClpP1P2 proteolytic complex (Gavrish et al., 2014).
The range of catalytically active serine hydrolases in an organism can be profiled by a chemoproteomic strategy termed activity-based protein profiling, wherein a warhead fluorophosphonate linked to a chemical handle containing a reporter tag is used to label the nucleophilic serine residue in active sites (Simon and Cravatt, 2010). Activitybased profiling has previously been used to probe the spectrum of M. tuberculosis adenosine binding proteins based on a reactive ATP analog (Ansong et al., 2013), and this approach has also been used to examine the importance of the essential serine/ threonine protein kinase PknB in bacterial replication and adaptation to hypoxic survival (Ortega et al., 2014). However, kinases pose challenging drug development targets due to the high conservation of their active sites, whereas serine hydrolases are a larger, more diverse family of enzymes with less conservation of their active site architecture (Simon and Cravatt, 2010). Ortega and colleagues (Ortega et al., 2016) utilized another fluorophosphonate-based probe to identify serine hydrolases in the fungal human pathogen Aspergillus fumigatus in response to host-relevant environmental stimuli (Wiedner et al., 2012). In the work reported in this issue (Ortega et al., 2016), labeling of M. tuberculosis proteins with this probe and subsequent click-chemistry catalyzed tagging of the alkyne to a biotin group with streptavidin-based purification revealed the labeling of 208 proteins, 78 of which were annotated as hydrolases or hypothetical proteins (Figure 1). The remaining 130
210 Cell Chemical Biology 23, February 18, 2016 ª2016 Elsevier Ltd All rights reserved
proteins had discrepant annotations. The group of 51 annotated hydrolases included the periplasmic protease MarP, critical for acid and oxidative stress resistance, which has previously been a subject of suicide inhibitor development (Zhao et al., 2015) and the lassomycin ClpP1/ClpP2 protease target (Gavrish et al., 2014). The catalytic activity of several of these annotated hydrolases provides functional confirmation of their activity. Importantly, their approach also identified proteins that were misannotated in the genome; for example, the product of the bpoC gene encoding an annotated peroxidase was labeled with the probe. This finding confirmed a structural study of this protein that had identified a typical hydrolase a-b fold with a serine-based catalytic triad (Johnston et al., 2010). The power of the activity-based proteomic profiling was further revealed in the characterization of 27 hypothetical proteins as serine hydrolases. Ortega and co-workers (Ortega et al., 2016) further confirmed the serine hydrolase function of these hypotheticals by in silico modeling of their predicted protein structure, which in several cases revealed a typical hydrolase fold, establishing caseinolytic activity for four of these and a phylogenetic analysis showing homology to hydrolase-like proteins. Rapid replication of M. tuberculosis cells from in vitro cultures does not accurately represent the spectrum of growth phases found in chronically infected human tuberculosis patients. To explore the opposite end of the spectrum of metabolic states, the fluorophosphonate probe was used to label proteins from hypoxic
Please cite this article as: Tonnus et al., ‘‘Death is my Heir’’—Ferroptosis Connects Cancer Pharmacogenomics and Ischemia-Reperfusion Injury, Cell Chemical Biology (2016), http://dx.doi.org/10.1016/j.chembiol.2016.02.001
Cell Chemical Biology
Previews
non-replicating cultures and compared to the labeled proteins from rapidly replicating cells (Figure 1). Interestingly, despite the apparent metabolic quiescence of non-replicating cells, 34 serine hydrolases were active under both conditions, 41 were specific for rapid growth, and 3 were specifically labeled in the non-replicating cells. The panel of panactive hydrolases included MarP and the ClpP2 subunit of the housekeeping proteolytic complex. This study provides the first preview of enzymes with a serine nucleophile in the active site that are catalytically active during growth as opposed to non-replicating persistence. It is noteworthy that the activity-based serine hydrolase profiling distinguishes active from expressed yet inert proteins. Correlation of peptide fragment abundance from total protein extracts to fragments from activity-labeled samples showed poor correlation, pointing to the regulation
of serine hydrolase activity by post-translational regulation. The identification of a panel of in vitro pan-active serine hydrolases feeds the pipeline of targets that can be exploited for suicide inhibitor development. ACKNOWLEDGMENTS
Johnston, J.M., Jiang, M., Guo, Z., and Baker, E.N. (2010). Acta Crystallogr. D Biol. Crystallogr. 66, 909–917. Ortega, C., Liao, R., Anderson, L.N., Rustad, T., Ollodart, A.R., Wright, A.T., Sherman, D.R., and Grundner, C. (2014). PLoS Biol. 12, e1001746. Ortega, C., Anderson, L.N., Frando, A., Sadler, N.C., Brown, R.W., Smith, R.D., Wright, A.T., and Grundner, C. (2016). Cell. Chem. Biol. 23, this issue, 290–298.
This work was funded by the Intramural Research Program of NIAID.
Simon, G.M., and Cravatt, B.F. (2010). J. Biol. Chem. 285, 11051–11055.
REFERENCES
Tipper, D.J., and Strominger, J.L. (1965). Proc. Natl. Acad. Sci. USA 54, 1133–1141.
Ansong, C., Ortega, C., Payne, S.H., Haft, D.H., Chauvigne`-Hines, L.M., Lewis, M.P., Ollodart, A.R., Purvine, S.O., Shukla, A.K., Fortuin, S., et al. (2013). Chem. Biol. 20, 123–133.
Wiedner, S.D., Burnum, K.E., Pederson, L.M., Anderson, L.N., Fortuin, S., Chauvigne´-Hines, L.M., Shukla, A.K., Ansong, C., Panisko, E.A., Smith, R.D., and Wright, A.T. (2012). J. Biol. Chem. 287, 33447–33459.
Bachovchin, D.A., and Cravatt, B.F. (2012). Nat. Rev. Drug Discov. 11, 52–68.
World Health Organization. (2015). Global Tuberculosis Report 2015 (World Health Organization).
Gavrish, E., Sit, C.S., Cao, S., Kandror, O., Spoering, A., Peoples, A., Ling, L., Fetterman, A., Hughes, D., Bissell, A., et al. (2014). Chem. Biol. 21, 509–518.
Zhao, N., Darby, C.M., Small, J., Bachovchin, D.A., Jiang, X., Burns-Huang, K.E., Botella, H., Ehrt, S., Boger, D.L., Anderson, E.D., et al. (2015). ACS Chem. Biol. 10, 364–371.
Computing Substrate Selectivity in a Peptide Transporter Claire Colas,1 David E. Smith,3 and Avner Schlessinger2,* 1Department
of Pharmacology and Systems Therapeutics of Pharmacology and Systems Therapeutics, and Structural and Chemical Biology Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA 3Department of Pharmaceutical Sciences, College of Pharmacy, University of Michigan, Ann Arbor, MI 48109, USA *Correspondence: [email protected] http://dx.doi.org/10.1016/j.chembiol.2016.02.001 2Departments
The human proton-coupled peptide transporter 1 (PepT1) is responsible for the absorption of di- and tri-peptides from the diet and peptide-like drugs. In this issue of Cell Chemical Biology, Samsudin et al. (2016) use an integrated computational and experimental approach to provide new insights into understanding substrate selectivity of PepTSt, a prokaryotic homolog of the human PepT1. In humans, there are presently 456 solute carrier (SLC) transporter genes from 52 families that modulate the import and efflux of a large variety of solutes across cell membranes, including amino acids, neurotransmitters, metabolites, ions, and drugs (Ce´sar-Razquin et al., 2015). PepT1 (SLC15A1) is a proton-coupled transporter of di- and tripeptides, primarily found in the small intestine, kidney, and pancreas, where it
absorbs a broad range of peptides from the diet and peptide-like drugs such as b-lactam antibiotics (Smith et al., 2013). PepT1 is also an emerging drug target. It is upregulated in the colons of patients with inflammatory bowel disease (IBD) where it transports bacterially derived products into colonic cytosol, thereby triggering an inflammatory response (Charrier and Merlin, 2006; Smith et al., 2013). Potential drugs tar-
geting PepT1 can be inhibitors that block the uptake of harmful peptides of bacterial origin or substrates that efficiently deliver anti-inflammatory prodrugs to the target site. The structure of the human PepT1 is unknown; however, structures of a prokaryotic homolog, PepTSt from Streptococcus thermophiles, have been determined in complex with di- and tri-peptides (Lyons et al., 2014). PepTSt has highly similar
Cell Chemical Biology 23, February 18, 2016 ª2016 Elsevier Ltd All rights reserved 211
Cell Chemical Biology
Previews
including the disease-causing species M. avium and M. abscessus, which further expands the biological importance of these findings. Future work will likely focus on determining the roles of these giant lipids in mycobacterial membrane function. Other mycobacterial trehalose lipids confer resistance to membrane desiccation (Harland et al., 2008), but this property probably depends on hydrogenbonding free hydroxyls, which are absent in TPP. On the other hand, TPP contains numerous cis-unsaturations, which disrupt lipid chain packing and suggest that changes in TPP content might modulate membrane fluidity, perhaps in response to environmental cues. A possible role for TPP in disease could be tested through deletion of the newly identified TPP biosynthetic genes in a virulent species like M. avium, followed by experimental infection.
ACKNOWLEDGMENTS This work was supported by 1R21AI103321 to J.C.S. and U19 111224, R01 116604, and a Gates Foundation Vaccine Accelerator Award to D.B.M.
REFERENCES Asselineau, C., Montrozier, H., and Prome´, J.C. (1969). Eur. J. Biochem. 10, 580–584. Asselineau, C.P., Montrozier, H.L., Prome´, J.C., Savagnac, A.M., and Welby, M. (1972). Eur. J. Biochem. 28, 102–109. Burbaud, S., Laval, F., Lemassu, A., Daffe´, M., Guilhot, C., and Chalut, C. (2016). Cell Chem. Biol. 23, this issue, 278–289. Harland, C.W., Rabuka, D., Bertozzi, C.R., and Parthasarathy, R. (2008). Biophys. J. 94, 4718– 4724. Layre, E., and Moody, D.B. (2013). Biochimie 95, 109–115. Layre, E., Sweet, L., Hong, S., Madigan, C.A., Desjardins, D., Young, D.C., Cheng, T.Y., An-
nand, J.W., Kim, K., Shamputa, I.C., et al. (2011). Chem. Biol. 18, 1537–1549. Sartain, M.J., Dick, D.L., Rithner, C.D., Crick, D.C., and Belisle, J.T. (2011). J. Lipid Res. 52, 861–872. Seeliger, J.C., Holsclaw, C.M., Schelle, M.W., Botyanszki, Z., Gilmore, S.A., Tully, S.E., Niederweis, M., Cravatt, B.F., Leary, J.A., and Bertozzi, C.R. (2012). J. Biol. Chem. 287, 7990–8000. Sonde´n, B., Kocı´ncova´, D., Deshayes, C., Euphrasie, D., Rhayat, L., Laval, F., Frehel, C., Daffe´, M., Etienne, G., and Reyrat, J.M. (2005). Mol. Microbiol. 58, 426–440. Touchette, M.H., Holsclaw, C.M., Previti, M.L., Solomon, V.C., Leary, J.A., Bertozzi, C.R., and Seeliger, J.C. (2015). J. Bacteriol. 197, 201–210. Vats, A., Singh, A.K., Mukherjee, R., Chopra, T., Ravindran, M.S., Mohanty, D., Chatterji, D., Reyrat, J.M., and Gokhale, R.S. (2012). J. Biol. Chem. 287, 30677–30687. Yadav, G., Gokhale, R.S., and Mohanty, D. (2003). J. Mol. Biol. 328, 335–363.
Uncovering the Serine Hydrolytic Landscape of Mycobacterium tuberculosis Helena I. Boshoff1,* 1Tuberculosis Research Section, Laboratory of Clinical Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA *Correspondence: [email protected] http://dx.doi.org/10.1016/j.chembiol.2016.02.002
In this issue of Cell Chemical Biology, Ortega et al. (2016) present a study utilizing a click-chemistry-enabled fluorophosphonate for activity-based identification of serine hydrolases, pinpointing a range of proteins including previously annotated hypotheticals. The application of this technology on both actively replicating and non-replicating Mycobacterium tuberculosis gives us a glimpse of its serine hydrolytic landscape during different stages of metabolic activity. Despite 60 years of anti-tubercular therapy, tuberculosis afflicts almost 10 million people annually, with 1.5 million deaths in 2014 (World Health Organization, 2015). The average duration for the treatment of drug-sensitive tuberculosis is 6 months and consists of a backbone regimen of rifampicin, pyrazinamide, and isoniazid, with a fourth agent to prevent emergence of drug resistance. The problems in clinical management of such an extensive therapy and the toxicities associated with
current anti-tubercular drugs contribute to non-compliance, which in turn is associated with relapse and emergence of drug resistance. The pipeline of drugs in clinical or pre-clinical development is limited, and it remains to be seen what the sterilizing potential of these agents will be in tuberculosis patients. The development of drugs that inactivate essential processes in both replicating as well as non- or slowlyreplicating bacilli, could conceptually contribute to treatment shortening.
Most metabolic inhibitors are competitive, non-competitive, or uncompetitive inhibitors of an enzyme, with the extent of inhibition in vivo dependent on concentrations of their substrate. Thus, the challenge in target-based drug discovery efforts is the identification of chokepoints in metabolism, whose partial inhibition has a catastrophic effect on bacterial metabolism. Inhibitors that form covalent adducts in the enzyme active site, in contrast, irreversibly
Cell Chemical Biology 23, February 18, 2016 ª2016 Elsevier Ltd All rights reserved 209
Please cite this article as: Tonnus et al., ‘‘Death is my Heir’’—Ferroptosis Connects Cancer Pharmacogenomics and Ischemia-Reperfusion Injury, Cell Chemical Biology (2016), http://dx.doi.org/10.1016/j.chembiol.2016.02.002
Cell Chemical Biology
Previews
Figure 1. A Chemoproteomic Approach to Labeling and Identifying Growth-Phase Dependent Serine Hydrolases in M. tuberculosis This figure illustrates a chemoproteomic approach using a fluorophosphonate activity-based probe (FP ABP) to label and identify serine hydrolases in M. tuberculosis during different growth phases. The FP ABP probe only labels serine hydrolases with a catalytically active serine, hereby distinguishing expressed yet inert protein from active enzyme.
inactivate the enzyme and can achieve full inhibition of the metabolic process. There are several examples of drugs that covalently modify their target, with b-lactams being classical examples of activity-based covalent inhibitors. b-lactams rely on their mimicry of the N-acyl-D-alanyl-D-alanine peptidoglycan peptide stems to acylate the active site nucleophilic serine of the transpeptidases involved in bacterial peptidoglycan cross-linking (Tipper and Strominger, 1965). Despite the general concern of reactivity for drugs that are covalent modifiers, high selectivity can be designed during inhibitor development based on substrate specificity of the enzyme. Serine hydrolases including the classical D,D-transpeptidases, but also a number of other enzymes including viral proteases, acetylcholinesterase, serine proteases critical for blood clotting, and dipeptidyl peptidase 4 have successfully been targeted in drug development using activity-based suicide inhibitors (Bachovchin and Cravatt, 2012). Essential serine hydrolases in Mycobacterium tuberculosis, the etiologic agent of tuberculosis, could potentially serve as starting points for rational drug design. In support of this, the discovery of lassomycin, which kills both replicating and non-replicating M. tuberculosis by binding to the N-terminal domain of the ClpC1 complex, thereby stimulating ATPase hydrolysis uncoupled from proteolysis, has demonstrated the utility of targeting serine hydrolases such as the essential ClpP1P2 proteolytic complex (Gavrish et al., 2014).
The range of catalytically active serine hydrolases in an organism can be profiled by a chemoproteomic strategy termed activity-based protein profiling, wherein a warhead fluorophosphonate linked to a chemical handle containing a reporter tag is used to label the nucleophilic serine residue in active sites (Simon and Cravatt, 2010). Activitybased profiling has previously been used to probe the spectrum of M. tuberculosis adenosine binding proteins based on a reactive ATP analog (Ansong et al., 2013), and this approach has also been used to examine the importance of the essential serine/ threonine protein kinase PknB in bacterial replication and adaptation to hypoxic survival (Ortega et al., 2014). However, kinases pose challenging drug development targets due to the high conservation of their active sites, whereas serine hydrolases are a larger, more diverse family of enzymes with less conservation of their active site architecture (Simon and Cravatt, 2010). Ortega and colleagues (Ortega et al., 2016) utilized another fluorophosphonate-based probe to identify serine hydrolases in the fungal human pathogen Aspergillus fumigatus in response to host-relevant environmental stimuli (Wiedner et al., 2012). In the work reported in this issue (Ortega et al., 2016), labeling of M. tuberculosis proteins with this probe and subsequent click-chemistry catalyzed tagging of the alkyne to a biotin group with streptavidin-based purification revealed the labeling of 208 proteins, 78 of which were annotated as hydrolases or hypothetical proteins (Figure 1). The remaining 130
210 Cell Chemical Biology 23, February 18, 2016 ª2016 Elsevier Ltd All rights reserved
proteins had discrepant annotations. The group of 51 annotated hydrolases included the periplasmic protease MarP, critical for acid and oxidative stress resistance, which has previously been a subject of suicide inhibitor development (Zhao et al., 2015) and the lassomycin ClpP1/ClpP2 protease target (Gavrish et al., 2014). The catalytic activity of several of these annotated hydrolases provides functional confirmation of their activity. Importantly, their approach also identified proteins that were misannotated in the genome; for example, the product of the bpoC gene encoding an annotated peroxidase was labeled with the probe. This finding confirmed a structural study of this protein that had identified a typical hydrolase a-b fold with a serine-based catalytic triad (Johnston et al., 2010). The power of the activity-based proteomic profiling was further revealed in the characterization of 27 hypothetical proteins as serine hydrolases. Ortega and co-workers (Ortega et al., 2016) further confirmed the serine hydrolase function of these hypotheticals by in silico modeling of their predicted protein structure, which in several cases revealed a typical hydrolase fold, establishing caseinolytic activity for four of these and a phylogenetic analysis showing homology to hydrolase-like proteins. Rapid replication of M. tuberculosis cells from in vitro cultures does not accurately represent the spectrum of growth phases found in chronically infected human tuberculosis patients. To explore the opposite end of the spectrum of metabolic states, the fluorophosphonate probe was used to label proteins from hypoxic
Please cite this article as: Tonnus et al., ‘‘Death is my Heir’’—Ferroptosis Connects Cancer Pharmacogenomics and Ischemia-Reperfusion Injury, Cell Chemical Biology (2016), http://dx.doi.org/10.1016/j.chembiol.2016.02.001
Cell Chemical Biology
Previews
non-replicating cultures and compared to the labeled proteins from rapidly replicating cells (Figure 1). Interestingly, despite the apparent metabolic quiescence of non-replicating cells, 34 serine hydrolases were active under both conditions, 41 were specific for rapid growth, and 3 were specifically labeled in the non-replicating cells. The panel of panactive hydrolases included MarP and the ClpP2 subunit of the housekeeping proteolytic complex. This study provides the first preview of enzymes with a serine nucleophile in the active site that are catalytically active during growth as opposed to non-replicating persistence. It is noteworthy that the activity-based serine hydrolase profiling distinguishes active from expressed yet inert proteins. Correlation of peptide fragment abundance from total protein extracts to fragments from activity-labeled samples showed poor correlation, pointing to the regulation
of serine hydrolase activity by post-translational regulation. The identification of a panel of in vitro pan-active serine hydrolases feeds the pipeline of targets that can be exploited for suicide inhibitor development. ACKNOWLEDGMENTS
Johnston, J.M., Jiang, M., Guo, Z., and Baker, E.N. (2010). Acta Crystallogr. D Biol. Crystallogr. 66, 909–917. Ortega, C., Liao, R., Anderson, L.N., Rustad, T., Ollodart, A.R., Wright, A.T., Sherman, D.R., and Grundner, C. (2014). PLoS Biol. 12, e1001746. Ortega, C., Anderson, L.N., Frando, A., Sadler, N.C., Brown, R.W., Smith, R.D., Wright, A.T., and Grundner, C. (2016). Cell. Chem. Biol. 23, this issue, 290–298.
This work was funded by the Intramural Research Program of NIAID.
Simon, G.M., and Cravatt, B.F. (2010). J. Biol. Chem. 285, 11051–11055.
REFERENCES
Tipper, D.J., and Strominger, J.L. (1965). Proc. Natl. Acad. Sci. USA 54, 1133–1141.
Ansong, C., Ortega, C., Payne, S.H., Haft, D.H., Chauvigne`-Hines, L.M., Lewis, M.P., Ollodart, A.R., Purvine, S.O., Shukla, A.K., Fortuin, S., et al. (2013). Chem. Biol. 20, 123–133.
Wiedner, S.D., Burnum, K.E., Pederson, L.M., Anderson, L.N., Fortuin, S., Chauvigne´-Hines, L.M., Shukla, A.K., Ansong, C., Panisko, E.A., Smith, R.D., and Wright, A.T. (2012). J. Biol. Chem. 287, 33447–33459.
Bachovchin, D.A., and Cravatt, B.F. (2012). Nat. Rev. Drug Discov. 11, 52–68.
World Health Organization. (2015). Global Tuberculosis Report 2015 (World Health Organization).
Gavrish, E., Sit, C.S., Cao, S., Kandror, O., Spoering, A., Peoples, A., Ling, L., Fetterman, A., Hughes, D., Bissell, A., et al. (2014). Chem. Biol. 21, 509–518.
Zhao, N., Darby, C.M., Small, J., Bachovchin, D.A., Jiang, X., Burns-Huang, K.E., Botella, H., Ehrt, S., Boger, D.L., Anderson, E.D., et al. (2015). ACS Chem. Biol. 10, 364–371.
Computing Substrate Selectivity in a Peptide Transporter Claire Colas,1 David E. Smith,3 and Avner Schlessinger2,* 1Department
of Pharmacology and Systems Therapeutics of Pharmacology and Systems Therapeutics, and Structural and Chemical Biology Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA 3Department of Pharmaceutical Sciences, College of Pharmacy, University of Michigan, Ann Arbor, MI 48109, USA *Correspondence: [email protected] http://dx.doi.org/10.1016/j.chembiol.2016.02.001 2Departments
The human proton-coupled peptide transporter 1 (PepT1) is responsible for the absorption of di- and tri-peptides from the diet and peptide-like drugs. In this issue of Cell Chemical Biology, Samsudin et al. (2016) use an integrated computational and experimental approach to provide new insights into understanding substrate selectivity of PepTSt, a prokaryotic homolog of the human PepT1. In humans, there are presently 456 solute carrier (SLC) transporter genes from 52 families that modulate the import and efflux of a large variety of solutes across cell membranes, including amino acids, neurotransmitters, metabolites, ions, and drugs (Ce´sar-Razquin et al., 2015). PepT1 (SLC15A1) is a proton-coupled transporter of di- and tripeptides, primarily found in the small intestine, kidney, and pancreas, where it
absorbs a broad range of peptides from the diet and peptide-like drugs such as b-lactam antibiotics (Smith et al., 2013). PepT1 is also an emerging drug target. It is upregulated in the colons of patients with inflammatory bowel disease (IBD) where it transports bacterially derived products into colonic cytosol, thereby triggering an inflammatory response (Charrier and Merlin, 2006; Smith et al., 2013). Potential drugs tar-
geting PepT1 can be inhibitors that block the uptake of harmful peptides of bacterial origin or substrates that efficiently deliver anti-inflammatory prodrugs to the target site. The structure of the human PepT1 is unknown; however, structures of a prokaryotic homolog, PepTSt from Streptococcus thermophiles, have been determined in complex with di- and tri-peptides (Lyons et al., 2014). PepTSt has highly similar
Cell Chemical Biology 23, February 18, 2016 ª2016 Elsevier Ltd All rights reserved 211