Development of robust analytical pipelines for the analysis of microbial community data from clinical samples

囊性纤维化是一种遗传性疾病，在英国约有9000人患有此病。这是一种隐性疾病，意味着父母双方都携带有缺陷的基因拷贝，孩子才会受到影响。大约每25人中就有1人携带这种基因。囊性纤维化极大地缩短了患者的寿命，几乎一半的患者活不过30岁。囊性纤维化对身体的许多部位都有负面影响，但对肺部的影响尤其严重。缺陷基因的结果是，厚厚的分泌物不能有效地从肺部清除，导致气道充血和受损。这种充血导致频繁和严重的恶化，有时需要住院治疗。我们认为病情恶化通常是感染的结果，而感染可能是由病毒和细菌引起的。最常见的细菌之一是铜绿假单胞菌。微生物学家诊断假单胞菌的方法是将样品的样品放在盘子上，并识别在可见菌落中生长的细菌。假单胞菌通常用抗生素治疗。其他细菌包括链球菌和葡萄球菌。然而，在寻找恶化的原因时，我们仅限于找到我们所知道的病原体，以及在我们使用的培养板上生长的病原体。可能还有其他细菌存在，我们看不见，因为它们不容易生长。有时这些细菌可能是病因。然而，就像人类的肠道一样，可能也有“好”和“坏”的细菌。众所周知，某些类型的细菌可以预防其他类型的感染，因此它们可能有助于防止病情恶化。一项新技术利用分子条形码的概念，从细胞内的DNA片段识别细菌种类。被称为高通量测序仪的新仪器允许从许多样品中轻松廉价地读取这些条形码。这项技术为我们提供了一个特定样本中细菌种类的“部分列表”，以及它们发生频率的大致概念。通过阅读这些囊性纤维化患者的部分列表——当他们健康时，当他们病得很重时，当他们正在康复时，我们可能能够告诉这些看不见的细菌对病情的相对贡献。例如，一个特定物种数量的增加或减少可能与恢复有关，这给了我们一个潜在的治疗目标。我们也很感兴趣，看看病人最终是如何被特定的、常见的细菌所感染的。例如，在我们当地的病人中，大约30%的人感染了一种叫做Midlands 1的假单胞菌。然而，对于如此多的患者最终被同一菌株感染的原因，人们知之甚少。我们现在能够对细菌细胞（基因组）中的所有DNA进行排序，这为它的进化提供了非常高的分辨率。通过比较来自不同患者的菌株基因组，我们可以帮助确定患者是用相同的菌株相互感染，还是菌株差异很大，来自许多不同的来源。我们还可以看到假单胞菌是如何在患者肺部进化的。先前的研究表明，假单胞菌适应特定的环境，这可能为我们提供线索，解释为什么具有相同囊性纤维化突变的人有不同的病程，最终入院或病情恶化的次数比其他人多。我们使用的技术是非常新的，在常规临床试验之前还有很多困难。一个问题是，机器会产生大量的测序“噪音”，这些噪音看起来像是存在的物种，但实际上并不存在。我想开发生物信息学方法，试图提高这些技术的可靠性，并产生对临床医生有用的信息。我们期望这些技术在未来五年内进入临床。

Cystic fibrosis is an inherited disease which affects around 9,000 people in the UK. It is a recessive disorder, meaning that both parents have to carry a faulty copy of a gene for a child to be affected. Approximately 1 in 25 people carry this copy. Cystic fibrosis dramatically shortens the life of those affected and almost half do not live beyond their 30s. Cystic fibrosis has a negative effect on many parts of the body, but it particularly affects the lungs. The result of the defective gene is that thick secretions cannot be effectively cleared from the lungs, resulting in the airways becoming congested and damaged.This congestion results in frequent and severe exacerbations, sometimes requiring admission to hospital and treatment. We think exacerbations are often a result of infections, which may be caused by viruses and bacteria. One of the most common bacteria found is Pseudomonas aeruginosa. Microbiologists diagnose Pseudomonas by putting samples of sample onto plates and identifying the bacteria that grow in visible colonies. Often Pseudomonas is treated by antibiotics. Other bacteria may be found including Streptococcus and Staphylococcus.However when looking for causes of exacerbations we are limited to finding pathogens that we know about, and which grow on the types of culture plates we use. It may be that other bacteria are present that we can't see because they do not grow easily. Sometimes those bacteria may be a cause. However, in a similar way to the human gut it may be that there are "good" and "bad" bacteria. It is known that certain types of bacteria can prevent other types infecting and therefore they may help protect against exacerbations.A new technology utilises the idea of molecular barcodes which identify bacterial species from fragments of DNA in their cell. New instruments termed high-throughput sequencers permit these barcodes to be read from many samples easily and cheaply. This technology gives us a "parts list" of the bacterial species in a particular sample, and a rough idea of how frequently they occur. By reading this parts lists from patients with cystic fibrosis - when they are well, when they are very sick and when they are recovering, we may be able to tell the relative contribution of these unseen bacteria to the condition. For example a particular species increasing or reducing in abundance may be associated with recovery, giving us a potential therapeutic target.We are also interesting in seeing how patients end up being colonised with particular, commonly seen bacteria. For example in our local patients, about 30% have a particular type of Pseudomonas infection called Midlands 1. However, very little is known about how it is that so many patients end up being infected by the same strain. We are now able to sequence all the DNA in a bacterial cell (the genome) which gives very high resolution view of how it has evolved. By comparing genomes of strains from different patients, we can help determine whether patients are infecting each other with the same strain, or whether the strains are quite different and come from many different sources. We can also see how the Pseudomonas evolves whilst it is in a patients lungs. Previous studies have shown that the Pseudomonas adapts to the specific environment, which may give us clues as to why people with the same cystic fibrosis mutation have different courses and end up with more hospital admissions or exacerbations than others.The technology we are using is very new, and there are a number of difficulties with it before it can be a routine clinical test. One problem is that the machines generate plenty of sequencing "noise" which may look like species are present that aren't. I want to develop bioinformatics methods that try and increase the reliability of these techniques and generate information that would be useful for clinicians. We expect these techniques to enter the clinic within the next five years.