Characterization of Periplasmic Iron Transport in Mycobacterium tuberculosis

周质间隙 铁载体 结核分枝杆菌 微生物学 生物化学 细菌外膜 化学 生物 肺结核 大肠杆菌 医学 基因 病理 有机化学
作者
Rodger de Miranda,Alex Chao,Paul J. Sieminski,Sumer Abdul‐Hafiz,Celia W. Goulding
出处
期刊:The FASEB Journal [Wiley]
卷期号:36 (S1)
标识
DOI:10.1096/fasebj.2022.36.s1.r4118
摘要

Tuberculosis (TB), caused by the bacterium Mycobacterium tuberculosis (Mtb), results in 10 million infections and 1.5 million deaths annually. Current TB treatments are typically a cocktail of up to five antibiotics that needs to be administered for a 9-month duration; unfortunately, several of these drugs illicit severe side effects. These long, harsh treatments lead to patient non-compliance resulting in a rise in multiple-drug resistant Mtb strains - MDR-TB. Due to these factors new treatment strategies are needed. As host iron acquisition is essential for Mtb's survival, elucidating key players in the Mtb iron uptake pathways may yield good drug targets. Mtb predominately acquires host iron by the siderophore-mediated uptake pathway, in which small molecules with high affinity for iron are secreted to scavenge for host iron. We seek to shed light on the mechanism by which ferric-siderophores are transported into the Mtb cytosol. At present there is little known about the proteins required to shuttle ferric-siderophores across the outer membrane, cell-wall environment, and periplasmic space to the inner membrane. There are two putative Mtb periplasmic binding proteins (PBPs), FecB and FecB2, and we hypothesize that one or both of these PBPs shuttle ferric-siderophores across the periplasmic space. To test this, we examined the affinity of FecB and FecB2 for the Mtb secreted ferric-siderophore, ferric-carboxymycobactin (Fe-cMB), by tryptophan fluorescence quenching titration assays. The affinity of FecB for Fe-cMB was in the high nanomolar range (Kd = 355 ± 146 nM); in contrast, the affinity of FecB2 was in the high micromolar range. This result suggests that FecB is involved in transporting Fe-cMB across the periplasmic space. To further probe the FecB residues involved in Fe-cMB binding, we carried out a comprehensive mutational analysis. In an attempt to decipher the protein-protein interaction network of FecB, we utilized co-immunopreciptation (co-IP) of FLAG-tagged FecB in the non-pathogenic Mtb model organism Mycobacterium smegmatis, followed by mass spectrometry analysis. The co-IP FLAG-FecB experiments resulted in identification of known proteins in the import of Fe-cMB and surprisingly, also proteins thought to be involved in the export of apo-siderophores. Together, these data clearly place FecB in the siderophore-mediated iron-uptake pathway, and will be discussed in more detail. Finally, this work has broadened our understanding of the Mtb iron acquisition pathway, which may lead to the identification of new therapeutic targets.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
听风完成签到,获得积分10
刚刚
刚刚
TOMORI酱发布了新的文献求助10
1秒前
hihi完成签到,获得积分10
1秒前
2秒前
朝暮完成签到 ,获得积分10
3秒前
彪壮的剑愁完成签到,获得积分10
3秒前
今后应助ziming313采纳,获得10
3秒前
潇洒莞完成签到 ,获得积分10
4秒前
所所应助窗外风雨阑珊采纳,获得10
4秒前
冷静孤容发布了新的文献求助10
6秒前
ding应助jy采纳,获得10
6秒前
敢敢发布了新的文献求助10
6秒前
7秒前
7秒前
孟奔奔完成签到 ,获得积分10
7秒前
深情安青应助蓝桉采纳,获得10
9秒前
11秒前
CipherSage应助11采纳,获得10
11秒前
orixero应助dream采纳,获得10
13秒前
wyw完成签到 ,获得积分10
14秒前
FashionBoy应助敢敢采纳,获得10
14秒前
CipherSage应助七柚采纳,获得10
14秒前
科研通AI5应助yulia采纳,获得10
14秒前
14秒前
在水一方应助正直姿采纳,获得10
14秒前
科研通AI2S应助赶路人采纳,获得10
16秒前
17秒前
17秒前
明明完成签到,获得积分10
19秒前
田様应助tttck采纳,获得10
19秒前
张达发布了新的文献求助10
19秒前
急雪回风应助优美从菡采纳,获得10
19秒前
李健应助我爱科研采纳,获得10
20秒前
领导范儿应助坦率访烟采纳,获得30
21秒前
Aaernan发布了新的文献求助10
22秒前
xiao完成签到,获得积分10
23秒前
23秒前
oMayii完成签到 ,获得积分10
25秒前
27秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Mechanistic Modeling of Gas-Liquid Two-Phase Flow in Pipes 2500
Kelsen’s Legacy: Legal Normativity, International Law and Democracy 1000
Conference Record, IAS Annual Meeting 1977 610
Interest Rate Modeling. Volume 3: Products and Risk Management 600
Interest Rate Modeling. Volume 2: Term Structure Models 600
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3542861
求助须知:如何正确求助?哪些是违规求助? 3120134
关于积分的说明 9341680
捐赠科研通 2818200
什么是DOI,文献DOI怎么找? 1549414
邀请新用户注册赠送积分活动 722131
科研通“疑难数据库(出版商)”最低求助积分说明 712978