With the rise of antimicrobial resistance (AMR), bacterial infections are a major threat to global public health. Tuberculosis, caused by the human pathogen Mycobacterium tuberculosis, is a case in point, with 1.6 million deaths worldwide (WHO, 2022), many of which are resistant to first- and second-line antibiotic treatments (Allué-Guardia et al., 2021; Hameed et al., 2018; Migliori et al., 2013). To successfully combat AMR there is a pressing and urgent need for alternative treatment strategies to failing antimicrobials. One such approach is offered by the development of host-derived therapies (HDTs), which target systems in the host rather than the pathogen, circumventing AMR (Kaufmann et al., 2018; Kilinç et al., 2021).

One primary immune defence against Mycobacterium tuberculosis (Mtb) is macrophages. Macrophages have a spectrum of phenotypes ranging from proinflammatory to anti-inflammatory, determined in a process known as macrophage polarisation. Mtb is expert at manipulation of macrophage polarisation to its advantage (Ahmad et al., 2022) and can inhibit the polarisation of proinflammatory macrophages, subverting killing mechanisms to promote intracellular survival of the bacteria and subsequent granuloma formation (Hackett et al., 2020). Reprogramming macrophages to better kill Mtb is a potential HDT strategy that may be particularly effective against intracellular pathogens (Sheedy and Divangahi, 2021).

Tribbles genes encode for a family of pseudokinases (TRIB1, TRIB2, and TRIB3; Kiss-Toth et al., 2004), involved in the regulation of core cellular processes, ranging from cell cycle to glucose metabolism (Grosshans and Wieschaus, 2000; Mata et al., 2000; Seher and Leptin, 2000). The TRIB1 isoform has been strongly associated with macrophage roles in inflammation and innate immunity (Johnston et al., 2015; Niespolo et al., 2020). TRIB1 regulates multiple important macrophage regulatory factors, especially controlling the proinflammatory response, such as tumour necrosis factor alpha (TNF-α), interleukin-1beta (IL-1β), and nitric oxide (NO) (Arndt et al., 2018; Liu et al., 2013). Trib1^−/− mice have decreased expression levels of inflammation-related genes such as IL-6, IL-1b, and Nos2 (encodes for inducible nitric oxide synthase, iNOS), and murine Trib1^−/− bone marrow-derived macrophages have defective inflammatory, phagocytic, migratory, and NO responses in vitro (Arndt et al., 2018; Liu et al., 2013).

TRIB1 influences inflammatory and immune processes via multiple mechanisms. The best described is via recruitment and binding of the E3 ubiquitin ligase constitutive photomorphogenic 1 (COP1). The TRIB1 protein possesses two functional binding sites in its C-terminal, one for COP1 and the second for mitogen-activated protein kinase kinase (MEK) binding. TRIB1 can act as a protein scaffold, binding a substrate to its pseudokinase domain, as well as binding in the functional C terminus to create a regulatory complex. Binding of TRIB1 to the E3 ubiquitin ligase COP1 causes a conformational change, enhancing COP1 binding and bringing COP1 into proximity with the substrate allowing ubiquitination and subsequent degradation (Jamieson et al., 2018; Kung and Jura, 2019; Murphy et al., 2015; Zahid et al., 2022). The TRIB1/COP1 complex is responsible for the regulation of multiple targets such as transcription factors, including the tumour suppressor CCAAT/enhancer-binding protein (C/EBPα), which regulates macrophage migration and TNF-α production (Liu et al., 2013; Yoshida et al., 2013).

While TRIB1 has been shown to regulate several inflammatory and innate immune functions in vitro, its role in infection is much less characterised, especially in an in vivo setting. TRIB1 is a predicted target of microRNA–gene interactions that differentiate active and latent TB patients (Wu et al., 2014) and is an overabundant transcript in highly proinflammatory tuberculosis-immune reconstitution inflammatory syndrome patients (Lai et al., 2015). However, despite these reported potential links between Tribbles and TB, interrogation of TRIB isoform transcripts in human mycobacterial datasets had not been performed.

Over the last two decades, the zebrafish has proved a powerful model for understanding host–pathogen interactions, due to its high-fecundity, transparency of larvae and availability of transgenic reporter lines. A human disease-relevant and tractable infection model is the zebrafish model of tuberculosis, utilising the injection of the natural fish pathogen Mycobacterium marinum (Mm), a close genetic relative of Mtb (Davis et al., 2002; van der Sar et al., 2009). This model has shed light on numerous immune pathways involved in host defence, for example hypoxia-inducible factor (HIF) signalling (Elks et al., 2013; Ogryzko et al., 2019; Schild et al., 2020).

Here, we show that Tribbles1 is expressed in human primary monocytes and its expression is increased at the site of a human in vivo mycobacterial antigen challenge, indicative of a role in TB responses. To substantiate the importance of TRIB1 in TB pathogenesis, we report a new, protective role for trib1 in infection defence using an in vivo zebrafish Mycobacterium marinum (Mm) infection model. Overexpression of trib1 significantly reduced Mm burden and increased production of the proinflammatory cytokine il1b and NO. The antimicrobial effect of trib1 overexpression was found to be dependent on cop1. Our findings uncover a role for trib1 in mycobacterial infection defence in vivo, highlighting Trib1 as a potential therapeutic target for manipulation to improve bacterial infection outcomes.

TRIB1 has previously been shown to be a key regulator of multiple inflammatory factors and immune cell function, influencing pathologies with an inflammatory component including cancer and atherosclerosis (Johnston et al., 2015). Innate immunity and production of inflammatory factors are important defence mechanisms against invading pathogens, yet the role of Tribbles in the immune response to infection is poorly understood. Here, we provide evidence that mycobacterial antigen stimulation both in vitro and in vivo induces human TRIB1 and TRIB2 expression independent of TB disease status. We used a zebrafish TB model to show that trib1 expression has functional roles in the innate immune response to infection in vivo. trib1 is required to control Mm infection, associated with increased production of the antimicrobial factors il-1β and NO. We also show a role for cop1, a binding partner of TRIB1, which is required for the host-protective effects of trib1 overexpression. The in vivo tools, developed here to investigate the immune roles of tribbles in zebrafish, create new opportunities to further investigate Tribbles1 as a potential therapeutic target, not only in infection, but in a wider range of disease contexts that have an innate immunity component.

For the first time, we have identified that Tribbles1 is important in the host response to mycobacterial infection, with TRIB1 being upregulated in human monocytes after mycobacterial antigen challenge and overexpression of trib1 being host-protective in a zebrafish TB model. TRIB1 is a well-known regulator of innate immune cells and functions in inflammatory settings playing a key role in the regulation of proinflammatory profiles (Arndt et al., 2018; Niespolo et al., 2020; Ostertag et al., 2010). Trib1^−/− mice have a defective inflammatory response, with reduced proinflammatory gene expression (including Nos2 and Il-1β compared to controls) resulting in bone-marrow-derived macrophages (BMDMs) that produce lower NO and have defective phagocytosis (Arndt et al., 2018). In zebrafish, trib1 overexpression increased production of proinflammatory factors, indicating that similar control of NO and Il-1β by TRIB1 is conserved in fish, although NO was primarily observed in neutrophils rather than macrophages matching previous observations in the zebrafish model (Elks et al., 2014; Elks et al., 2013).

TRIB1 has been associated with inflammation and immune response, whereas TRIB3 is strongly associated with metabolic function, including the regulation of glucose homeostasis (Angyal and Kiss-Toth, 2012; Prudente et al., 2012; Zhang et al., 2013) which also has regulatory roles in innate immune cells such as macrophages (Steverson et al., 2016; Wang et al., 2012). There are robust links between glucose metabolism and innate immune responses, such as the glycolytic switch which is closely related to macrophage polarisation (Zhu et al., 2015). Immune cell glucose and lipid metabolism have important roles in infection defence. Lipid droplets form in macrophages during Mtb infection that are potentially used as source of lipids by Mtb to allow for intracellular growth (Daniel et al., 2011). However, more recent findings suggest that lipid droplets are formed during the immune activation process after macrophage Mtb infection (Knight et al., 2018), that can subsequently influence the dynamic response of macrophage host defence (Menon et al., 2019). In murine atheroma models, Trib1 increased the lipid accumulation in macrophages leading to the formation of foam cells (Johnston et al., 2019). In Drosophila melanogaster, trbl knockdown increased circulating triglyceride levels (Das et al., 2014) and in mice where TRIB3 knockdown in a murine adipose cell line (3T3-L1) increased intracellular triglycerides (Takahashi et al., 2008) and targeted deletion of murine TRIB3 resulted in elevated triglyceride levels in the liver (Örd et al., 2018). Macrophage lipid metabolism and handling during Mtb infection could therefore potentially be influenced by Tribbles.

It is interesting to note that overexpression or knockdown of trib genes did not affect macrophage and neutrophil differentiation in zebrafish larvae. Trib1-deficient mice have been shown to have defects in the differentiation of a number of different immune cells, including an increase in neutrophils due to commitment of the granulocyte precursor lineage to neutrophils at the expense of eosinophils (Mack et al., 2019) and a decrease in M2-like tissue-resident macrophages (Satoh et al., 2013). The effects of Trib1 deficiency on eosinophil/neutrophil differentiation has been shown to be dependent on C/EBP transcription factors (Mack et al., 2019). Similar to mammalian neutrophil differentiation, zebrafish neutrophil differentiation is partially regulated by C/EBP transcription factors including Cebpα (Dai et al., 2016; Yuan et al., 2011), Cebp1 (the functional homolog of mammalian C/EBPε, Kim et al., 2016) and Cebpβ (Wei et al., 2020). It was therefore surprising that trib1 manipulation did not affect neutrophil differentiation in the zebrafish and highlights potential differences between the function of zebrafish trib1 compared to murine TRIB1. An important C/EBP in zebrafish myelopoiesis is a zebrafish-specific isoform called Cebp1 that is myeloid expressed (Lyons et al., 2001). This has a highly conserved carboxy-terminal bZIP domain with mammalian homologues, but the amino-terminal domains are unique. Reduction of Cebp1 did not ablate initial macrophage or granulocyte development in 24 hpf zebrafish larvae (Lyons et al., 2001). Recent findings demonstrate that Cebp1 controls eosinophilopoiesis in zebrafish larvae and has important roles in balancing the neutrophil and eosinophil lineages (Li et al., 2024), as in mice (Mack et al., 2019), however, eosinophils do not emerge until after 5 dpf beyond the stages in our study (Balla et al., 2010; Li et al., 2024). It remains unclear as to whether M2-like macrophages are affected by trib1 modulation in zebrafish as they are in mice (Satoh et al., 2013), as biomarkers/transgenic tools to investigate the existence of M2-like macrophages in larvae have only recently been developed (Hammond et al., 2023), but could be of interest in future studies.

Many of the reported regulatory functions of TRIB1 in immune cells are dependent on COP1 (Kung and Jura, 2019). In our zebrafish Mm model the protective effect of trib1 overexpression was reduced when cop1 was depleted, demonstrating a requirement for cop1 expression to improve the host response to infection. Interestingly, cop1 CRISPants possess a subtly reduced burden compared to controls without the overexpression of trib1, suggesting that cop1 depletion alone may offer a small level of protection. In cancer cell lines infected with Mycobacterium bovis Bacillus Calmette–Guérin (BCG), BCG-induced Sonic Hedgehog signalling increasing COP1 expression, leading to the inhibition of apoptosis in the cell line (Holla et al., 2014), indicating there may be a COP1 response to mycobacterial infection. The TRIB1/COP1 complex is responsible for the regulation of multiple targets, including C/EBPs (Liu et al., 2013; Yoshida et al., 2013). The lack of changes observed in neutrophil and macrophage numbers in trib1/cop1 knockdowns in our zebrafish studies, discussed above, may be suggestive of C/EBP independent mechanisms. There is evidence suggesting that COP1 and C/EBP have distinct binding sites on TRIB1, potentially unlinking their activity in some biological situations and this may be the case in zebrafish haematopoeisis (Murphy et al., 2015). There are many other candidate pathways other than C/EBPs that Trib1 and Cop1 interactions can influence that could lead to the host-protective effect observed, with examples including mitogen-activated protein kinases (Niespolo et al., 2020), serine threonine kinases (Durzynska et al., 2017), JAK/STAT (Arndt et al., 2018), and beta-Catenin (Zahid et al., 2022), likely context and cell dependent. For example, the neutrophil NO response generated by trib1 overexpression in zebrafish could be produced through JAK/STAT signalling which, in mice, regulates macrophage NO via TRIB1 control of STAT3 and STAT6 (Arndt et al., 2018). The zebrafish will be a useful in vivo model to investigate and dissect these pathways further.

If proinflammatory signals are initiated early in infection, this can reduce infection burden and improve infection outcomes. An example of this is control of the proinflammatory response by HIF-1α, where early stabilisation and activation of HIF-1α signalling is host beneficial in mycobacterial infection (Elks et al., 2013; Lewis and Elks, 2019; Ogryzko et al., 2019). The host-protective effect of trib1 overexpression closely mimicked the effects of Hif-1α stabilisation, with an increase in the production of antimicrobial factors NO and il-1β and a decrease in Mm infection burden (Elks et al., 2013; Ogryzko et al., 2019). TRIB3 has been associated with HIF-1α in renal cell carcinoma patients with HIF-1α binding to multiple regions in the TRIB3 promoter resulting in upregulation of TRIB3 expression (Hong et al., 2019). In lung adenocarcinoma cells, TRIB3 knockdown decreased levels of HIF-1α (Xing et al., 2020), indicating a feedback loop between TRIB3 and HIF-1α, where one can regulate the other. In common with TRIB3, a potential link between TRIB2 and HIF-1α has been reported, as depletion of TRIB2 significantly decreased the effect of TNF-α on HIF-1α stability and accumulation in multiple cancer cell lines (Schoolmeesters et al., 2012). However, there is no current link identified between TRIB1 and HIF-1α and this was reflected in our findings showing that trib1 overexpression did not lead to an increase in a well-validated Hif-α reporter line (Santhakumar et al., 2012).

Together our findings show a potential therapeutic application of targeting Trib1 to improve infection outcomes. We demonstrate il-1b and NO control by Trib1, suggesting that Trib1 controls multiple immune pathways and that therapeutic Trib1 manipulation may be more effective than targeting individual immune pathways alone. Due to its potential functions in multiple pathways, any targeting of Trib1 must be carefully controlled. For example, overexpression of TRIB1 in chronic mycobacterial infections may be beneficial against infection, but could trigger immunopathology. The concept of host immunomodulation is an emerging therapeutic avenue for infectious disease, especially with the continually increasing problem of AMR in multiple pathogens, and could potentially be used alongside antimicrobial drug treatment. To aid the efficiency of host immunomodulation, and to help avoid off-target effects, specific targeting methods can be used. Polymersomes have been shown to be a promising avenue for drug delivery to immune cells and could be utilised for the delivery of host immunomodulatory compounds and factors (Dal et al., 2020). Further research into TRIB1 as a target for host-derived therapies could potentially improve infection outcome of mycobacterial infection via pharmacological targeted delivery methods and transient manipulation through genetic approaches.

All data generated or analysed during this study are included in the manuscript, supporting files and source data. Expression data was derived from publicly available transcriptomic data deposited in EBI ArrayExpress repository (datasets E-MTAB-8162 and E-MTAB-6816 respectively - https://www.ebi.ac.uk/biostudies/arrayexpresshttps://www.ebi.ac.uk/biostudies/arrayexpress). Original gel images can be found in Figure 4—figure supplement 2—source data 1,2, Figure 4—figure supplement 3—source data 1 and Figure 8—figure supplement 1—source data 1. Figure 1—source data 1–9, Figure 4—source data 1–5, Figure 4—figure supplement 3—source data 2, Figure 5—source data 1–6, Figure 6—source data 1,2, Figure 8—source data 1,2, and Figure 8—figure supplement 1—source data 2 contain the numerical data used to generate the figures.

1. 1. Pollara G

   (2021) EBI ArrayExpress

   ID E-MTAB-8162. Monocytes from people with active or latent TB stimulated in vitro with PPD.

   https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-8162
2. 1. Pollara G

   (2019) EBI ArrayExpress

   ID E-MTAB-6816. Transcriptional profiling of the tuberculin skin test in patients with active and latent tuberculosis.

   https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-6816

1. 1. Ahmad F
   2. Rani A
   3. Alam A
   4. Zarin S
   5. Pandey S
   6. Singh H
   7. Hasnain SE
   8. Ehtesham NZ

   (2022) Macrophage: a cell with many faces and functions in tuberculosis

   Frontiers in Immunology 13:747799.

   https://doi.org/10.3389/fimmu.2022.747799

   • PubMed
   • Google Scholar
2. 1. Allué-Guardia A
   2. Saranathan R
   3. Chan J
   4. Torrelles JB

   (2021) Mycobacteriophages as potential therapeutic agents against drug-resistant tuberculosis

   International Journal of Molecular Sciences 22:E735.

   https://doi.org/10.3390/ijms22020735

   • PubMed
   • Google Scholar
3. 1. Angyal A
   2. Kiss-Toth E

   (2012) The tribbles gene family and lipoprotein metabolism

   Current Opinion in Lipidology 23:122–126.

   https://doi.org/10.1097/MOL.0b013e3283508c3b

   • PubMed
   • Google Scholar
4. 1. Arndt L
   2. Dokas J
   3. Gericke M
   4. Kutzner CE
   5. Müller S
   6. Jeromin F
   7. Thiery J
   8. Burkhardt R

   (2018) Tribbles homolog 1 deficiency modulates function and polarization of murine bone marrow-derived macrophages

   The Journal of Biological Chemistry 293:11527–11536.

   https://doi.org/10.1074/jbc.RA117.000703

   • PubMed
   • Google Scholar
5. 1. Athanasiadis EI
   2. Botthof JG
   3. Andres H
   4. Ferreira L
   5. Lio P
   6. Cvejic A

   (2017) Single-cell RNA-sequencing uncovers transcriptional states and fate decisions in haematopoiesis

   Nature Communications 8:2045.

   https://doi.org/10.1038/s41467-017-02305-6

   • PubMed
   • Google Scholar
6. 1. Balla KM
   2. Lugo-Villarino G
   3. Spitsbergen JM
   4. Stachura DL
   5. Hu Y
   6. Bañuelos K
   7. Romo-Fewell O
   8. Aroian RV
   9. Traver D

   (2010) Eosinophils in the zebrafish: prospective isolation, characterization, and eosinophilia induction by helminth determinants

   Blood 116:3944–3954.

   https://doi.org/10.1182/blood-2010-03-267419

   • PubMed
   • Google Scholar
7. 1. Bell LCK
   2. Pollara G
   3. Pascoe M
   4. Tomlinson GS
   5. Lehloenya RJ
   6. Roe J
   7. Meldau R
   8. Miller RF
   9. Ramsay A
   10. Chain BM
   11. Dheda K
   12. Noursadeghi M

   (2016) In vivo molecular dissection of the effects of HIV-1 in Active Tuberculosis

   PLOS Pathogens 12:e1005469.

   https://doi.org/10.1371/journal.ppat.1005469

   • PubMed
   • Google Scholar
8. 1. Benard EL
   2. van der Sar AM
   3. Ellett F
   4. Lieschke GJ
   5. Spaink HP
   6. Meijer AH

   (2012) Infection of zebrafish embryos with intracellular bacterial pathogens

   Journal of Visualized Experiments 01:3781.

   https://doi.org/10.3791/3781

   • PubMed
   • Google Scholar
9. 1. Bernut A
   2. Dupont C
   3. Ogryzko NV
   4. Neyret A
   5. Herrmann JL
   6. Floto RA
   7. Renshaw SA
   8. Kremer L

   (2019) CFTR protects against mycobacterium abscessus infection by fine-tuning host oxidative defenses

   Cell Reports 26:1828–1840.

   https://doi.org/10.1016/j.celrep.2019.01.071

   • PubMed
   • Google Scholar
10. 1. Bojarczuk A
    2. Miller KA
    3. Hotham R
    4. Lewis A
    5. Ogryzko NV
    6. Kamuyango AA
    7. Frost H
    8. Gibson RH
    9. Stillman E
    10. May RC
    11. Renshaw SA
    12. Johnston SA

    (2016) Cryptococcus neoformans intracellular proliferation and capsule size determines early macrophage control of infection

    Scientific Reports 6:21489.

    https://doi.org/10.1038/srep21489

    • PubMed
    • Google Scholar
11. 1. Buchan KD
    2. Prajsnar TK
    3. Ogryzko NV
    4. de Jong NWM
    5. van Gent M
    6. Kolata J
    7. Foster SJ
    8. van Strijp JAG
    9. Renshaw SA

    (2019) A transgenic zebrafish line for in vivo visualisation of neutrophil myeloperoxidase

    PLOS ONE 14:e0215592.

    https://doi.org/10.1371/journal.pone.0215592

    • PubMed
    • Google Scholar
12. 1. Dai X
    2. Ding Y
    3. Liu Z
    4. Zhang W
    5. Zou MH

    (2016) Phosphorylation of CHOP (C/EBP Homologous Protein) by the AMP-activated protein Kinase Alpha 1 in macrophages promotes chop degradation and reduces injury-induced neointimal disruption in vivo

    Circulation Research 119:1089–1100.

    https://doi.org/10.1161/CIRCRESAHA.116.309463

    • PubMed
    • Google Scholar
13. 1. Dal N-JK
    2. Kocere A
    3. Wohlmann J
    4. Van Herck S
    5. Bauer TA
    6. Resseguier J
    7. Bagherifam S
    8. Hyldmo H
    9. Barz M
    10. De Geest BG
    11. Fenaroli F

    (2020) Zebrafish embryos allow prediction of nanoparticle circulation times in mice and facilitate quantification of nanoparticle-cell interactions

    Small 16:e1906719.

    https://doi.org/10.1002/smll.201906719

    • PubMed
    • Google Scholar
14. 1. Daniel J
    2. Maamar H
    3. Deb C
    4. Sirakova TD
    5. Kolattukudy PE

    (2011) Mycobacterium tuberculosis uses host triacylglycerol to accumulate lipid droplets and acquires a dormancy-like phenotype in lipid-loaded macrophages

    PLOS Pathogens 7:e1002093.

    https://doi.org/10.1371/journal.ppat.1002093

    • PubMed
    • Google Scholar
15. 1. Das R
    2. Sebo Z
    3. Pence L
    4. Dobens LL

    (2014) Drosophila tribbles antagonizes insulin signaling-mediated growth and metabolism via interactions with Akt kinase

    PLOS ONE 9:e109530.

    https://doi.org/10.1371/journal.pone.0109530

    • PubMed
    • Google Scholar
16. 1. Davis JM
    2. Clay H
    3. Lewis JL
    4. Ghori N
    5. Herbomel P
    6. Ramakrishnan L

    (2002) Real-time visualization of mycobacterium-macrophage interactions leading to initiation of granuloma formation in zebrafish embryos

    Immunity 17:693–702.

    https://doi.org/10.1016/s1074-7613(02)00475-2

    • PubMed
    • Google Scholar
17. 1. Durzynska I
    2. Xu X
    3. Adelmant G
    4. Ficarro SB
    5. Marto JA
    6. Sliz P
    7. Uljon S
    8. Blacklow SC

    (2017) STK40 Is a Pseudokinase that binds the E3 ubiquitin ligase COP1

    Structure 25:287–294.

    https://doi.org/10.1016/j.str.2016.12.008

    • PubMed
    • Google Scholar
18. 1. Elks PM
    2. Loynes CA
    3. Renshaw SA

    (2011) Measuring inflammatory cell migration in the zebrafish

    Methods in Molecular Biology 769:261–275.

    https://doi.org/10.1007/978-1-61779-207-6_18

    • PubMed
    • Google Scholar
19. 1. Elks PM
    2. Brizee S
    3. van der Vaart M
    4. Walmsley SR
    5. van Eeden FJ
    6. Renshaw SA
    7. Meijer AH

    (2013) Hypoxia inducible factor signaling modulates susceptibility to mycobacterial infection via a nitric oxide dependent mechanism

    PLOS Pathogens 9:e1003789.

    https://doi.org/10.1371/journal.ppat.1003789

    • Google Scholar
20. 1. Elks PM
    2. van der Vaart M
    3. van Hensbergen V
    4. Schutz E
    5. Redd MJ
    6. Murayama E
    7. Spaink HP
    8. Meijer AH

    (2014) Mycobacteria counteract a TLR-mediated nitrosative defense mechanism in a zebrafish infection model

    PLOS ONE 9:e100928.

    https://doi.org/10.1371/journal.pone.0100928

    • PubMed
    • Google Scholar
21. 1. Forlenza M
    2. Scharsack JP
    3. Kachamakova NM
    4. Taverne-Thiele AJ
    5. Rombout JHWM
    6. Wiegertjes GF

    (2008) Differential contribution of neutrophilic granulocytes and macrophages to nitrosative stress in a host-parasite animal model

    Mol Immunol 45:3178–3189.

    https://doi.org/10.1016/j.molimm.2008.02.025

    • Google Scholar
22. 1. Grosshans J
    2. Wieschaus E

    (2000) A genetic link between morphogenesis and cell division during formation of the ventral furrow in Drosophila

    Cell 101:523–531.

    https://doi.org/10.1016/s0092-8674(00)80862-4

    • Google Scholar
23. 1. Hackett EE
    2. Charles-Messance H
    3. O’Leary SM
    4. Gleeson LE
    5. Muñoz-Wolf N
    6. Case S
    7. Wedderburn A
    8. Johnston DGW
    9. Williams MA
    10. Smyth A
    11. Ouimet M
    12. Moore KJ
    13. Lavelle EC
    14. Corr SC
    15. Gordon SV
    16. Keane J
    17. Sheedy FJ

    (2020) Mycobacterium tuberculosis limits host glycolysis and IL-1β by restriction of PFK-M via MicroRNA-21

    Cell Reports 30:124–136.

    https://doi.org/10.1016/j.celrep.2019.12.015

    • PubMed
    • Google Scholar
24. 1. Hameed S
    2. Mahmood N
    3. Chaudhry MN
    4. Ahmad SR
    5. Rahman MA

    (2018)

    Molecular detection of mutations in isolates of multidrug resistant tuberculosis and tuberculosis suspects by multiplex allele specific PCR

    Pakistan Journal of Pharmaceutical Sciences 31:2661–2666.

    • PubMed
    • Google Scholar
25. 1. Hammond FR
    2. Lewis A
    3. Speirs ZC
    4. Anderson HE
    5. Sipka T
    6. Williams LG
    7. Nguyen-Chi M
    8. Meijer AH
    9. Wiegertjes GF
    10. Elks PM

    (2023) An arginase 2 promoter transgenic line illuminates immune cell polarisation in zebrafish

    Disease Models & Mechanisms 16:dmm049966.

    https://doi.org/10.1242/dmm.049966

    • PubMed
    • Google Scholar
26. 1. Hegedus Z
    2. Czibula A
    3. Kiss-Toth E

    (2006) Tribbles: novel regulators of cell function; evolutionary aspects

    Cellular and Molecular Life Sciences 63:1632–1641.

    https://doi.org/10.1007/s00018-006-6007-9

    • PubMed
    • Google Scholar
27. 1. Hegedus Z
    2. Czibula A
    3. Kiss-Toth E

    (2007) Tribbles: a family of kinase-like proteins with potent signalling regulatory function

    Cellular Signalling 19:238–250.

    https://doi.org/10.1016/j.cellsig.2006.06.010

    • PubMed
    • Google Scholar
28. 1. Holla S
    2. Ghorpade DS
    3. Singh V
    4. Bansal K
    5. Balaji KN

    (2014) Mycobacterium bovis BCG promotes tumor cell survival from tumor necrosis factor-α-induced apoptosis

    Molecular Cancer 13:210.

    https://doi.org/10.1186/1476-4598-13-210

    • PubMed
    • Google Scholar
29. 1. Hong B
    2. Zhou J
    3. Ma K
    4. Zhang J
    5. Xie H
    6. Zhang K
    7. Li L
    8. Cai L
    9. Zhang N
    10. Zhang Z
    11. Gong K

    (2019) TRIB3 promotes the proliferation and invasion of renal cell carcinoma cells via activating MAPK signaling pathway

    International Journal of Biological Sciences 15:587–597.

    https://doi.org/10.7150/ijbs.29737

    • PubMed
    • Google Scholar
30. 1. Hruscha A
    2. Krawitz P
    3. Rechenberg A
    4. Heinrich V
    5. Hecht J
    6. Haass C
    7. Schmid B

    (2013) Efficient CRISPR/Cas9 genome editing with low off-target effects in zebrafish

    Developmen 140:4982–4987.

    https://doi.org/10.1242/dev.099085

    • PubMed
    • Google Scholar
31. 1. Isles HM
    2. Herman KD
    3. Robertson AL
    4. Loynes CA
    5. Prince LR
    6. Elks PM
    7. Renshaw SA

    (2019) The CXCL12/CXCR4 signaling axis retains neutrophils at inflammatory sites in Zebrafish

    Frontiers in Immunology 10:1784.

    https://doi.org/10.3389/fimmu.2019.01784

    • PubMed
    • Google Scholar
32. 1. Jamieson SA
    2. Ruan Z
    3. Burgess AE
    4. Curry JR
    5. McMillan HD
    6. Brewster JL
    7. Dunbier AK
    8. Axtman AD
    9. Kannan N
    10. Mace PD

    (2018) Substrate binding allosterically relieves autoinhibition of the pseudokinase TRIB1

    Science Signaling 11:eaau0597.

    https://doi.org/10.1126/scisignal.aau0597

    • Google Scholar
33. 1. Johnston J
    2. Basatvat S
    3. Ilyas Z
    4. Francis S
    5. Kiss-Toth E

    (2015) Tribbles in inflammation

    Biochemical Society Transactions 43:1069–1074.

    https://doi.org/10.1042/BST20150095

    • PubMed
    • Google Scholar
34. 1. Johnston JM
    2. Angyal A
    3. Bauer RC
    4. Hamby S
    5. Suvarna SK
    6. Baidžajevas K
    7. Hegedus Z
    8. Dear TN
    9. Turner M
    10. Cardiogenics Consortium
    11. Wilson HL
    12. Goodall AH
    13. Rader DJ
    14. Shoulders CC
    15. Francis SE
    16. Kiss-Toth E

    (2019) Myeloid Tribbles 1 induces early atherosclerosis via enhanced foam cell expansion

    Science Advances 5:eaax9183.

    https://doi.org/10.1126/sciadv.aax9183

    • PubMed
    • Google Scholar
35. 1. Jumper J
    2. Evans R
    3. Pritzel A
    4. Green T
    5. Figurnov M
    6. Ronneberger O
    7. Tunyasuvunakool K
    8. Bates R
    9. Žídek A
    10. Potapenko A
    11. Bridgland A
    12. Meyer C
    13. Kohl SAA
    14. Ballard AJ
    15. Cowie A
    16. Romera-Paredes B
    17. Nikolov S
    18. Jain R
    19. Adler J
    20. Back T
    21. Petersen S
    22. Reiman D
    23. Clancy E
    24. Zielinski M
    25. Steinegger M
    26. Pacholska M
    27. Berghammer T
    28. Bodenstein S
    29. Silver D
    30. Vinyals O
    31. Senior AW
    32. Kavukcuoglu K
    33. Kohli P
    34. Hassabis D

    (2021) Highly accurate protein structure prediction with AlphaFold

    Nature 596:583–589.

    https://doi.org/10.1038/s41586-021-03819-2

    • PubMed
    • Google Scholar
36. 1. Kaufmann E
    2. Sanz J
    3. Dunn JL
    4. Khan N
    5. Mendonça LE
    6. Pacis A
    7. Tzelepis F
    8. Pernet E
    9. Dumaine A
    10. Grenier JC
    11. Mailhot-Léonard F
    12. Ahmed E
    13. Belle J
    14. Besla R
    15. Mazer B
    16. King IL
    17. Nijnik A
    18. Robbins CS
    19. Barreiro LB
    20. Divangahi M

    (2018) BCG educates hematopoietic stem cells to generate protective innate immunity against tuberculosis

    Cell 172:176–190.

    https://doi.org/10.1016/j.cell.2017.12.031

    • PubMed
    • Google Scholar
37. 1. Kilinç G
    2. Saris A
    3. Ottenhoff THM
    4. Haks MC

    (2021) Host-directed therapy to combat mycobacterial infections

    Immunological Reviews 301:62–83.

    https://doi.org/10.1111/imr.12951

    • PubMed
    • Google Scholar
38. 1. Kim KW
    2. Thakur N
    3. Piggott CA
    4. Omi S
    5. Polanowska J
    6. Jin Y
    7. Pujol N

    (2016) Coordinated inhibition of C/EBP by Tribbles in multiple tissues is essential for Caenorhabditis elegans development

    BMC Biology 14:104.

    https://doi.org/10.1186/s12915-016-0320-z

    • PubMed
    • Google Scholar
39. 1. Kiss-Toth E
    2. Bagstaff SM
    3. Sung HY
    4. Jozsa V
    5. Dempsey C
    6. Caunt JC
    7. Oxley KM
    8. Wyllie DH
    9. Polgar T
    10. Harte M
    11. O’neill LAJ
    12. Qwarnstrom EE
    13. Dower SK

    (2004) Human tribbles, a protein family controlling mitogen-activated protein kinase cascades

    The Journal of Biological Chemistry 279:42703–42708.

    https://doi.org/10.1074/jbc.M407732200

    • PubMed
    • Google Scholar
40. 1. Knight M
    2. Braverman J
    3. Asfaha K
    4. Gronert K
    5. Stanley S

    (2018) Lipid droplet formation in Mycobacterium tuberculosis infected macrophages requires IFN-γ/HIF-1α signaling and supports host defense

    PLOS Pathogens 14:e1006874.

    https://doi.org/10.1371/journal.ppat.1006874

    • PubMed
    • Google Scholar
41. 1. Kung JE
    2. Jura N

    (2019) The pseudokinase TRIB1 toggles an intramolecular switch to regulate COP1 nuclear export

    The EMBO Journal 38:e99708.

    https://doi.org/10.15252/embj.201899708

    • PubMed
    • Google Scholar
42. 1. Lai RPJ
    2. Meintjes G
    3. Wilkinson KA
    4. Graham CM
    5. Marais S
    6. Van der Plas H
    7. Deffur A
    8. Schutz C
    9. Bloom C
    10. Munagala I
    11. Anguiano E
    12. Goliath R
    13. Maartens G
    14. Banchereau J
    15. Chaussabel D
    16. O’Garra A
    17. Wilkinson RJ

    (2015) HIV-tuberculosis-associated immune reconstitution inflammatory syndrome is characterized by Toll-like receptor and inflammasome signalling

    Nature Communications 6:8451.

    https://doi.org/10.1038/ncomms9451

    • PubMed
    • Google Scholar
43. 1. Lewis A
    2. Elks PM

    (2019) Hypoxia induces macrophage tnfa expression via cyclooxygenase and prostaglandin E2 in vivo

    Frontiers in Immunology 10:2321.

    https://doi.org/10.3389/fimmu.2019.02321

    • Google Scholar
44. 1. Li G
    2. Sun Y
    3. Kwok I
    4. Yang L
    5. Wen W
    6. Huang P
    7. Wu M
    8. Li J
    9. Huang Z
    10. Liu Z
    11. He S
    12. Peng W
    13. Bei JX
    14. Ginhoux F
    15. Ng LG
    16. Zhang Y

    (2024) Cebp1 and Cebpβ transcriptional axis controls eosinophilopoiesis in zebrafish

    Nature Communications 15:811.

    https://doi.org/10.1038/s41467-024-45029-0

    • Google Scholar
45. 1. Liu Y-H
    2. Tan KAL
    3. Morrison IW
    4. Lamb JR
    5. Argyle DJ

    (2013) Macrophage migration is controlled by Tribbles 1 through the interaction between C/EBPβ and TNF-α

    Veterinary Immunology and Immunopathology 155:67–75.

    https://doi.org/10.1016/j.vetimm.2013.06.001

    • Google Scholar
46. 1. Lyons SE
    2. Shue BC
    3. Oates AC
    4. Zon LI
    5. Liu PP

    (2001) A novel myeloid-restricted zebrafish CCAAT/enhancer-binding protein with A potent transcriptional activation domain

    Blood 97:2611–2617.

    https://doi.org/10.1182/blood.v97.9.2611

    • PubMed
    • Google Scholar
47. 1. Mack EA
    2. Stein SJ
    3. Rome KS
    4. Xu L
    5. Wertheim GB
    6. Melo RCN
    7. Pear WS

    (2019) Trib1 regulates eosinophil lineage commitment and identity by restraining the neutrophil program

    Blood 133:2413–2426.

    https://doi.org/10.1182/blood.2018872218

    • PubMed
    • Google Scholar
48. 1. Mata J
    2. Curado S
    3. Ephrussi A
    4. Rørth P

    (2000) Tribbles coordinates mitosis and morphogenesis in Drosophila by regulating string/CDC25 proteolysis

    Cell 101:511–522.

    https://doi.org/10.1016/s0092-8674(00)80861-2

    • PubMed
    • Google Scholar
49. 1. Menon D
    2. Singh K
    3. Pinto SM
    4. Nandy A
    5. Jaisinghani N
    6. Kutum R
    7. Dash D
    8. Prasad TSK
    9. Gandotra S

    (2019) Quantitative lipid droplet proteomics reveals mycobacterium tuberculosis induced alterations in macrophage response to infection

    ACS Infectious Diseases 5:559–569.

    https://doi.org/10.1021/acsinfecdis.8b00301

    • PubMed
    • Google Scholar
50. 1. Migliori GB
    2. Centis R
    3. D’Ambrosio L

    (2013) A case of resistance beyond extensively drug-resistant tuberculosis in Japan

    The European Respiratory Journal 42:872–873.

    https://doi.org/10.1183/09031936.00061113

    • PubMed
    • Google Scholar
51. 1. Murphy JM
    2. Nakatani Y
    3. Jamieson SA
    4. Dai W
    5. Lucet IS
    6. Mace PD

    (2015) Molecular mechanism of CCAAT-Enhancer binding protein recruitment by the TRIB1 Pseudokinase

    Structure 23:2111–2121.

    https://doi.org/10.1016/j.str.2015.08.017

    • PubMed
    • Google Scholar
52. 1. Niespolo C
    2. Johnston JM
    3. Deshmukh SR
    4. Satam S
    5. Shologu Z
    6. Villacanas O
    7. Sudbery IM
    8. Wilson HL
    9. Kiss-Toth E

    (2020) Tribbles-1 expression and its function to control inflammatory cytokines, including interleukin-8 levels are regulated by miRNAs in macrophages and prostate cancer cells

    Frontiers in Immunology 11:574046.

    https://doi.org/10.3389/fimmu.2020.574046

    • Google Scholar
53. 1. Noguchi K
    2. Yokozeki K
    3. Tanaka Y
    4. Suzuki Y
    5. Nakajima K
    6. Nishimura T
    7. Goda N

    (2022) Sima, a Drosophila homolog of HIF-1α, in fat body tissue inhibits larval body growth by inducing Tribbles gene expression

    Genes Cells 27:145–151.

    https://doi.org/10.1111/gtc.12913

    • Google Scholar
54. 1. Ogryzko NV
    2. Lewis A
    3. Wilson HL
    4. Meijer AH
    5. Renshaw SA
    6. Elks PM

    (2019) Hif-1α-induced expression of Il-1β protects against mycobacterial infection in Zebrafish

    Journal of Immunology 202:494–502.

    https://doi.org/10.4049/jimmunol.1801139

    • PubMed
    • Google Scholar
55. 1. Örd T
    2. Örd D
    3. Örd T

    (2018) TRIB3 limits FGF21 induction during in vitro and in vivo nutrient deficiencies by inhibiting C/EBP–ATF response elements in the FGF21 promoter

    Biochimica et Biophysica Acta 1861:271–281.

    https://doi.org/10.1016/j.bbagrm.2018.01.014

    • Google Scholar
56. 1. Örd T
    2. Puurand T
    3. Örd D
    4. Annilo T
    5. Möls M
    6. Remm M
    7. Örd T

    (2020) A human-specific VNTR in the TRIB3 promoter causes gene expression variation between individuals

    PLOS Genetics 16:e1008981.

    https://doi.org/10.1371/journal.pgen.1008981

    • Google Scholar
57. 1. Ostertag A
    2. Jones A
    3. Rose AJ
    4. Liebert M
    5. Kleinsorg S
    6. Reimann A
    7. Vegiopoulos A
    8. Berriel Diaz M
    9. Strzoda D
    10. Yamamoto M
    11. Satoh T
    12. Akira S
    13. Herzig S

    (2010) Control of adipose tissue inflammation through TRB1

    Diabetes 59:1991–2000.

    https://doi.org/10.2337/db09-1537

    • PubMed
    • Google Scholar
58. 1. Pettersen EF
    2. Goddard TD
    3. Huang CC
    4. Meng EC
    5. Couch GS
    6. Croll TI
    7. Morris JH
    8. Ferrin TE

    (2021) UCSF ChimeraX: Structure visualization for researchers, educators, and developers

    Protein Science 30:70–82.

    https://doi.org/10.1002/pro.3943

    • PubMed
    • Google Scholar
59. 1. Pollara G
    2. Turner CT
    3. Rosenheim J
    4. Chandran A
    5. Bell LCK
    6. Khan A
    7. Patel A
    8. Peralta LF
    9. Folino A
    10. Akarca A
    11. Venturini C
    12. Baker T
    13. Ecker S
    14. Ricciardolo FLM
    15. Marafioti T
    16. Ugarte-Gil C
    17. Moore DAJ
    18. Chain BM
    19. Tomlinson GS
    20. Noursadeghi M

    (2021) Exaggerated IL-17A activity in human in vivo recall responses discriminates active tuberculosis from latent infection and cured disease

    Science Translational Medicine 13:eabg7673.

    https://doi.org/10.1126/scitranslmed.abg7673

    • PubMed
    • Google Scholar
60. 1. Prudente S
    2. Sesti G
    3. Pandolfi A
    4. Andreozzi F
    5. Consoli A
    6. Trischitta V

    (2012) The mammalian tribbles homolog TRIB3, glucose homeostasis, and cardiovascular diseases

    Endocrine Reviews 33:526–546.

    https://doi.org/10.1210/er.2011-1042

    • PubMed
    • Google Scholar
61. 1. Qi L
    2. Heredia JE
    3. Altarejos JY
    4. Screaton R
    5. Goebel N
    6. Niessen S
    7. MacLeod IX
    8. Liew CW
    9. Kulkarni RN
    10. Bain J
    11. Newgard C
    12. Nelson M
    13. Evans RM
    14. Yates J
    15. Montminy M

    (2006) TRB3 links the E3 ubiquitin ligase COP1 to lipid metabolism

    Science 312:1763–1766.

    https://doi.org/10.1126/science.1123374

    • Google Scholar
62. 1. Renshaw SA
    2. Loynes CA
    3. Trushell DMI
    4. Elworthy S
    5. Ingham PW
    6. Whyte MKB

    (2006) A transgenic zebrafish model of neutrophilic inflammation

    Blood 108:3976–3978.

    https://doi.org/10.1182/blood-2006-05-024075

    • PubMed
    • Google Scholar
63. 1. Santhakumar K
    2. Judson EC
    3. Elks PM
    4. McKee S
    5. Elworthy S
    6. van Rooijen E
    7. Walmsley SS
    8. Renshaw SA
    9. Cross SS
    10. van Eeden FJM

    (2012) A zebrafish model to study and therapeutically manipulate hypoxia signaling in tumorigenesis

    Cancer Research 72:4017–4027.

    https://doi.org/10.1158/0008-5472.CAN-11-3148

    • PubMed
    • Google Scholar
64. 1. Satoh T
    2. Kidoya H
    3. Naito H
    4. Yamamoto M
    5. Takemura N
    6. Nakagawa K
    7. Yoshioka Y
    8. Morii E
    9. Takakura N
    10. Takeuchi O
    11. Akira S

    (2013) Critical role of Trib1 in differentiation of tissue-resident M2-like macrophages

    Nature 495:524–528.

    https://doi.org/10.1038/nature11930

    • PubMed
    • Google Scholar
65. 1. Schild Y
    2. Mohamed A
    3. Wootton EJ
    4. Lewis A
    5. Elks PM

    (2020) Hif-1alpha stabilisation is protective against infection in zebrafish comorbid models

    The FEBS Journal 287:3925–3943.

    https://doi.org/10.1111/febs.15433

    • PubMed
    • Google Scholar
66. 1. Schindelin J
    2. Arganda-Carreras I
    3. Frise E
    4. Kaynig V
    5. Longair M
    6. Pietzsch T
    7. Preibisch S
    8. Rueden C
    9. Saalfeld S
    10. Schmid B
    11. Tinevez JY
    12. White DJ
    13. Hartenstein V
    14. Eliceiri K
    15. Tomancak P
    16. Cardona A

    (2012) Fiji: an open-source platform for biological-image analysis

    Nature Methods 9:676–682.

    https://doi.org/10.1038/nmeth.2019

    • PubMed
    • Google Scholar
67. 1. Schoolmeesters A
    2. Brown DD
    3. Fedorov Y

    (2012) Kinome-wide functional genomics screen reveals a novel mechanism of TNFα-induced nuclear accumulation of the HIF-1α transcription factor in cancer cells

    PLOS ONE 7:e31270.

    https://doi.org/10.1371/journal.pone.0031270

    • PubMed
    • Google Scholar
68. 1. Seher TC
    2. Leptin M

    (2000) Tribbles, a cell-cycle brake that coordinates proliferation and morphogenesis during Drosophila gastrulation

    Current Biology 10:623–629.

    https://doi.org/10.1016/S0960-9822(00)00502-9

    • Google Scholar
69. 1. Sheedy FJ
    2. Divangahi M

    (2021) Targeting immunometabolism in host defence against Mycobacterium tuberculosis

    Immunology 162:145–159.

    https://doi.org/10.1111/imm.13276

    • Google Scholar
70. 1. Steverson D
    2. Tian L
    3. Fu Y
    4. Zhang W
    5. Ma E
    6. Garvey WT

    (2016) Tribbles homolog 3 promotes foam cell formation associated with decreased proinflammatory cytokine production in macrophages: Evidence for reciprocal regulation of cholesterol uptake and inflammation

    Metabolic Syndrome and Related Disorders 14:7–15.

    https://doi.org/10.1089/met.2015.0037

    • PubMed
    • Google Scholar
71. 1. Stoop EJM
    2. Schipper T
    3. Rosendahl Huber SK
    4. Nezhinsky AE
    5. Verbeek FJ
    6. Gurcha SS
    7. Besra GS
    8. Vandenbroucke-Grauls CMJE
    9. Bitter W
    10. van der Sar AM

    (2011) Zebrafish embryo screen for mycobacterial genes involved in the initiation of granuloma formation reveals a newly identified ESX-1 component

    Disease Models & Mechanisms 4:526–536.

    https://doi.org/10.1242/dmm.006676

    • PubMed
    • Google Scholar
72. 1. Takahashi Y
    2. Ohoka N
    3. Hayashi H
    4. Sato R

    (2008) TRB3 suppresses adipocyte differentiation by negatively regulating PPARgamma transcriptional activity

    Journal of Lipid Research 49:880–892.

    https://doi.org/10.1194/jlr.M700545-JLR200

    • PubMed
    • Google Scholar
73. 1. Thisse C
    2. Thisse B

    (2008) High-resolution in situ hybridization to whole-mount zebrafish embryos

    Nature Protocols 3:59–69.

    https://doi.org/10.1038/nprot.2007.514

    • PubMed
    • Google Scholar
74. 1. van der Sar AM
    2. Spaink HP
    3. Zakrzewska A
    4. Bitter W
    5. Meijer AH

    (2009) Specificity of the zebrafish host transcriptome response to acute and chronic mycobacterial infection and the role of innate and adaptive immune components

    Molecular Immunology 46:2317–2332.

    https://doi.org/10.1016/j.molimm.2009.03.024

    • PubMed
    • Google Scholar
75. 1. Varadi M
    2. Anyango S
    3. Deshpande M
    4. Nair S
    5. Natassia C
    6. Yordanova G
    7. Yuan D
    8. Stroe O
    9. Wood G
    10. Laydon A
    11. Žídek A
    12. Green T
    13. Tunyasuvunakool K
    14. Petersen S
    15. Jumper J
    16. Clancy E
    17. Green R
    18. Vora A
    19. Lutfi M
    20. Figurnov M
    21. Cowie A
    22. Hobbs N
    23. Kohli P
    24. Kleywegt G
    25. Birney E
    26. Hassabis D
    27. Velankar S

    (2022) AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models

    Nucleic Acids Research 50:D439–D444.

    https://doi.org/10.1093/nar/gkab1061

    • PubMed
    • Google Scholar
76. 1. Wang Z
    2. Shang Y
    3. Zhang S
    4. Zhong M
    5. Wang X
    6. Deng J
    7. Pan J
    8. Zhang Y
    9. Zhang W

    (2012) Silence of TRIB3 suppresses atherosclerosis and stabilizes plaques in diabetic ApoE-/-/LDL receptor-/- mice

    Diabetes 61:463–473.

    https://doi.org/10.2337/db11-0518

    • PubMed
    • Google Scholar
77. 1. Wei K
    2. Luo J
    3. Cao J
    4. Peng L
    5. Ren L
    6. Zhang F

    (2020) Adiponectin protects obese rats from aggravated acute lung injury via suppression of endoplasmic reticulum stress

    Diabetes, Metabolic Syndrome and Obesity 13:4179–4190.

    https://doi.org/10.2147/DMSO.S278684

    • PubMed
    • Google Scholar
78. 1. Wennemers M
    2. Bussink J
    3. Scheijen B
    4. Nagtegaal ID
    5. van Laarhoven HWM
    6. Raleigh JA
    7. Varia MA
    8. Heuvel J
    9. Rouschop KM
    10. Sweep F
    11. Span PN

    (2011) Tribbles homolog 3 denotes a poor prognosis in breast cancer and is involved in hypoxia response

    Breast Cancer Research 13:R82.

    https://doi.org/10.1186/bcr2934

    • PubMed
    • Google Scholar
79. Website

    1. WHO

    (2022) Global tuberculosis report 2022

    Accessed October 27, 2022.

    https://www.who.int/publications/i/item/9789240061729
80. 1. Wu LSH
    2. Lee SW
    3. Huang KY
    4. Lee TY
    5. Hsu PWC
    6. Weng JTY

    (2014) Systematic expression profiling analysis identifies specific microRNA-gene interactions that may differentiate between active and latent tuberculosis infection

    BioMed Research International 2014:895179.

    https://doi.org/10.1155/2014/895179

    • PubMed
    • Google Scholar
81. 1. Xing Y
    2. Luo P
    3. Hu R
    4. Wang D
    5. Zhou G
    6. Jiang J

    (2020) TRIB3 promotes lung adenocarcinoma progression via an enhanced warburg effect

    Cancer Management and Research 12:13195–13206.

    https://doi.org/10.2147/CMAR.S287956

    • PubMed
    • Google Scholar
82. 1. Yokoyama T
    2. Kanno Y
    3. Yamazaki Y
    4. Takahara T
    5. Miyata S
    6. Nakamura T

    (2010) Trib1 links the MEK1/ERK pathway in myeloid leukemogenesis

    Blood 116:2768–2775.

    https://doi.org/10.1182/blood-2009-10-246264

    • PubMed
    • Google Scholar
83. 1. Yoshida A
    2. Kato JY
    3. Nakamae I
    4. Yoneda-Kato N

    (2013) COP1 targets C/EBPα for degradation and induces acute myeloid leukemia via Trib1

    Blood 122:1750–1760.

    https://doi.org/10.1182/blood-2012-12-476101

    • PubMed
    • Google Scholar
84. 1. Yuan H
    2. Zhou J
    3. Deng M
    4. Zhang Y
    5. Chen Y
    6. Jin Y
    7. Zhu J
    8. Chen SJ
    9. de The H
    10. Chen Z
    11. Liu TX
    12. Zhu J

    (2011) Sumoylation of CCAAT/enhancer-binding protein α promotes the biased primitive hematopoiesis of zebrafish

    Blood 117:7014–7020.

    https://doi.org/10.1182/blood-2010-12-325712

    • PubMed
    • Google Scholar
85. 1. Zahid S
    2. Basharat S
    3. Fakhar M
    4. Rashid S

    (2022) Molecular dynamics and structural analysis of the binding of COP1 E3 ubiquitin ligase to β-catenin and TRIB pseudokinases

    Proteins 90:993–1004.

    https://doi.org/10.1002/prot.26292

    • PubMed
    • Google Scholar
86. 1. Zhang W
    2. Liu J
    3. Tian L
    4. Liu Q
    5. Fu Y
    6. Garvey WT

    (2013) TRIB3 mediates glucose-induced insulin resistance via a mechanism that requires the hexosamine biosynthetic pathway

    Diabetes 62:4192–4200.

    https://doi.org/10.2337/db13-0312

    • PubMed
    • Google Scholar
87. 1. Zhu L
    2. Zhao Q
    3. Yang T
    4. Ding W
    5. Zhao Y

    (2015) Cellular metabolism and macrophage functional polarization

    International Reviews of Immunology 34:82–100.

    https://doi.org/10.3109/08830185.2014.969421

    • PubMed
    • Google Scholar

Author details

1. Ffion R Hammond

   The Bateson Centre, School of Medicine and Population Health, Faculty of Health, University of Sheffield, Sheffield, United Kingdom

   Contribution

   Conceptualization, Resources, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing

   Competing interests

   No competing interests declared

2. Amy Lewis

   The Bateson Centre, School of Medicine and Population Health, Faculty of Health, University of Sheffield, Sheffield, United Kingdom

   Contribution

   Conceptualization, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-1156-3592

3. Gabriele Pollara

   Division of Infection & Immunity, University College London, London, United Kingdom

   Contribution

   Conceptualization, Resources, Data curation, Formal analysis, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing

   Competing interests

   No competing interests declared

4. Gillian S Tomlinson

   Division of Infection & Immunity, University College London, London, United Kingdom

   Contribution

   Conceptualization, Resources, Data curation, Formal analysis, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-4342-3161

5. Mahdad Noursadeghi

   Division of Infection & Immunity, University College London, London, United Kingdom

   Contribution

   Conceptualization, Resources, Data curation, Formal analysis, Funding acquisition, Validation, Investigation, Visualization, Methodology, Project administration, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4774-0853

6. Endre Kiss-Toth

   The Bateson Centre, School of Medicine and Population Health, Faculty of Health, University of Sheffield, Sheffield, United Kingdom

   Contribution

   Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing

   For correspondence

   e.kiss-toth@sheffield.ac.uk

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-4406-4017

7. Philip M Elks

   The Bateson Centre, School of Medicine and Population Health, Faculty of Health, University of Sheffield, Sheffield, United Kingdom

   Contribution

   Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing

   For correspondence

   p.elks@sheffield.ac.uk

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1683-0749

• 405

  views

• 79

  downloads

• 0

  citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.