Joe DeRisi: Hunting the next killer virus

30,372 views ・ 2009-01-30

TED


请双击下面的英文字幕来播放视频。

翻译人员: xiaomei he 校对人员: Xu Jiang
00:12
How can we investigate
0
12160
3000
怎么说呢?我们应该如何来研究
00:15
this flora of viruses that surround us, and aid medicine?
1
15160
5000
那些围绕在我们身边,又同时帮助医学发展的病毒?
00:20
How can we turn our cumulative knowledge of virology
2
20160
4000
我们怎样才能把我们积累的有关病毒的知识
00:24
into a simple, hand-held, single diagnostic assay?
3
24160
4000
变成简单、可行的方法运用到诊断中去?
00:28
I want to turn everything we know right now about detecting viruses
4
28160
3000
我想将所有我们现在已知的有关检测病毒
00:31
and the spectrum of viruses that are out there
5
31160
2000
和病毒图谱的方法
00:33
into, let's say, a small chip.
6
33160
3000
变成,比如说,一块小小的芯片。
00:36
When we started thinking about this project --
7
36160
2000
当我们开始思考这个计划时 -
00:38
how we would make a single diagnostic assay
8
38160
3000
我就在想我们如何通过一个简单的诊断
00:41
to screen for all pathogens simultaneously --
9
41160
3000
将所有的病原体同时检测出来 -
00:44
well, there's some problems with this idea.
10
44160
2000
其实这个想法实施起来有一些困难。
00:46
First of all, viruses are pretty complex,
11
46160
4000
首先,病毒是相当复杂的,
00:50
but they're also evolving very fast.
12
50160
4000
同时它们的进化速度相当快。
00:54
This is a picornavirus.
13
54160
1000
这是一种小核糖核酸病毒
00:55
Picornaviruses -- these are things that include
14
55160
2000
小核糖核酸病毒包括了
00:57
the common cold and polio, things like this.
15
57160
3000
普通感冒和小儿麻痹症之类的病症。
01:00
You're looking at the outside shell of the virus,
16
60160
2000
你们仔细看病毒的外壳
01:02
and the yellow color here are those parts of the virus
17
62160
3000
这些黄色的部分
01:05
that are evolving very, very fast,
18
65160
2000
进化得很快,非常快,
01:07
and the blue parts are not evolving very fast.
19
67160
2000
而那些蓝色的部分则进化得相对缓慢。
01:09
When people think about making pan-viral detection reagents,
20
69160
3000
当人们想到制造泛用型病毒检测剂时
01:12
usually it's the fast-evolving problem that's an issue,
21
72160
4000
病毒的快速演变是个问题,
01:16
because how can we detect things if they're always changing?
22
76160
2000
因为我们如何能够对一直变化着的病毒进行检测呢?
01:18
But evolution is a balance:
23
78160
2000
但是进化是一种平衡:
01:20
where you have fast change, you also have ultra-conservation --
24
80160
4000
哪里有快速变化,哪里也会有超级保守 -
01:24
things that almost never change.
25
84160
2000
有些东西几乎是不变的。
01:26
And so we looked into this a little more carefully,
26
86160
3000
所以我们要再看仔细些,
01:29
and I'm going to show you data now.
27
89160
1000
现在我要向你们展示一些数据。
01:30
This is just some stuff you can do on the computer from the desktop.
28
90160
3000
这些东西你在桌子的电脑上就可以完成。
01:33
I took a bunch of these small picornaviruses,
29
93160
2000
我将一些小核糖核酸病毒
01:35
like the common cold, like polio and so on,
30
95160
2000
如普通感冒和小儿麻痹症等
01:37
and I just broke them down into small segments.
31
97160
4000
分割成小的片段,
01:41
And so took this first example, which is called coxsackievirus,
32
101160
3000
第一个例子是柯萨奇病毒,
01:44
and just break it into small windows.
33
104160
2000
我将它们放到小玻璃片上,
01:46
And I'm coloring these small windows blue
34
106160
2000
然后我将这些小玻璃染成蓝色
01:48
if another virus shares an identical sequence in its genome
35
108160
5000
如果有另一个病毒有着和那个病毒相同的
01:53
to that virus.
36
113160
1000
基因序列.
01:54
These sequences right up here --
37
114160
2000
这里的序列——
01:56
which don't even code for protein, by the way --
38
116160
2000
顺便说一句,这些序列甚至没有同蛋白质编码-
01:58
are almost absolutely identical across all of these,
39
118160
3000
几乎完全与所有这些相同,
02:01
so I could use this sequence as a marker
40
121160
4000
所以我将这个序列做为一个标记物
02:05
to detect a wide spectrum of viruses,
41
125160
2000
来检测更多的病毒,
02:07
without having to make something individual.
42
127160
3000
不需要再进行个别实验。
02:10
Now, over here there's great diversity:
43
130160
2000
在那些进化迅速的地方
02:12
that's where things are evolving fast.
44
132160
2000
你会看到很大的差异,
02:14
Down here you can see slower evolution: less diversity.
45
134160
4000
在这里你可以看到缓慢的变化和较小的差异。
02:18
Now, by the time we get out here to, let's say,
46
138160
2000
现在我们再看看别的,比如说
02:20
acute bee paralysis virus --
47
140160
2000
蜜蜂急性肠道病毒
02:22
probably a bad one to have if you're a bee ---
48
142160
2000
这应该是蜜蜂界中最严重病毒-
02:24
this virus shares almost no similarity to coxsackievirus,
49
144160
5000
这种病毒和柯萨奇病毒几乎没有任何相似之处,
02:29
but I can guarantee you that the sequences that are most conserved
50
149160
4000
但是我可以向你保证在右侧屏幕中的病毒中的
02:33
among these viruses on the right-hand of the screen
51
153160
2000
最保守的基因序列
02:35
are in identical regions right up here.
52
155160
3000
都在相同的区域里。
02:38
And so we can encapsulate these regions of ultra-conservation
53
158160
3000
因此我们可以简述这些进化中的超保守区域 -
02:41
through evolution -- how these viruses evolved --
54
161160
3000
这些病毒如何进化的——
02:44
by just choosing DNA elements or RNA elements
55
164160
3000
仅通过选择这些区域的DNA或RNA片段
02:47
in these regions to represent on our chip as detection reagents.
56
167160
4000
作为检测试剂在我们的芯片上表现出来。
02:51
OK, so that's what we did, but how are we going to do that?
57
171160
3000
那是我们所做的,但我们如何去做呢?
02:54
Well, for a long time, since I was in graduate school,
58
174160
2000
很长时间以来,自从我读研究生
02:56
I've been messing around making DNA chips --
59
176160
3000
我一直在试验DNA芯片 -
02:59
that is, printing DNA on glass.
60
179160
2000
即在玻璃上打印DNA。
03:01
And that's what you see here:
61
181160
1000
你们看,就是这个:
03:02
These little salt spots are just DNA tacked onto glass,
62
182160
3000
这些小的盐点是DNA留在玻璃上的印记,
03:05
and so I can put thousands of these on our glass chip
63
185160
3000
同样我可以在玻璃芯片上放上千个盐点
03:08
and use them as a detection reagent.
64
188160
2000
然后把它们作为检测试剂。
03:10
We took our chip over to Hewlett-Packard
65
190160
2000
我们把芯片带到惠普公司,
03:12
and used their atomic force microscope on one of these spots,
66
192160
2000
用他们的原子显微镜来观察其中的一个点,
03:14
and this is what you see:
67
194160
2000
你们看到的就是这个:
03:16
you can actually see the strands of DNA lying flat on the glass here.
68
196160
3000
你们能很清楚地看到在玻璃上的DNA链,
03:19
So, what we're doing is just printing DNA on glass --
69
199160
3000
所以我们现在所做的就是将DNA打印在玻璃上,
03:22
little flat things -- and these are going to be markers for pathogens.
70
202160
4000
那些又小又平的东西是要作为病原体的标记物。
03:26
OK, I make little robots in lab to make these chips,
71
206160
3000
我在实验室里用小机器人来制造这些芯片,
03:29
and I'm really big on disseminating technology.
72
209160
3000
我真的非常热衷于传播科技。
03:32
If you've got enough money to buy just a Camry,
73
212160
3000
如果你刚好有钱去买一辆凯美瑞汽车,
03:35
you can build one of these too,
74
215160
2000
那你也可以制造一个这个,
03:37
and so we put a deep how-to guide on the Web, totally free,
75
217160
4000
我们在网站上有个免费的如何做的指南,
03:41
with basically order-off-the-shelf parts.
76
221160
2000
附带基本的组件订购部分 -
03:43
You can build a DNA array machine in your garage.
77
223160
3000
你可以在你的车库里生产一个DNA芯片机器。
03:46
Here's the section on the all-important emergency stop switch.
78
226160
3000
这部分是所有重要的紧急开关。
03:49
(Laughter)
79
229160
2000
(笑声)
03:51
Every important machine's got to have a big red button.
80
231160
3000
每个重要的机器都有一个大的红色按钮。
03:54
But really, it's pretty robust.
81
234160
2000
但真的,非常坚固。
03:56
You can actually be making DNA chips in your garage
82
236160
3000
你可以在你的车库里制作DNA芯片,
03:59
and decoding some genetic programs pretty rapidly. It's a lot of fun.
83
239160
4000
快速解码一些遗传程序。非常有趣。
04:03
(Laughter)
84
243160
1000
(笑声)
04:04
And so what we did -- and this is a really cool project --
85
244160
4000
所以我们做的——是一个非常酷的项目——
04:08
we just started by making a respiratory virus chip.
86
248160
2000
我们是从制作呼吸道病毒芯片开始的。
04:10
I talked about that --
87
250160
2000
我讲的是
04:12
you know, that situation where you go into the clinic
88
252160
2000
你知道,那种情况,你进了诊所,
04:14
and you don't get diagnosed?
89
254160
2000
但没有得到诊断。
04:16
Well, we just put basically all the human respiratory viruses
90
256160
2000
好,我们刚好把所有人类呼吸道病毒
04:18
on one chip, and we threw in herpes virus for good measure --
91
258160
3000
放在一张芯片上,然后又加入疱疹病毒以更好的测定。
04:21
I mean, why not?
92
261160
1000
为什么不呢?
04:22
The first thing you do as a scientist is,
93
262160
2000
作为一个科学家第一件要做的事就是
04:24
you make sure stuff works.
94
264160
1000
确定你要做的工作。
04:25
And so what we did is, we take tissue culture cells
95
265160
3000
我们所做的就是提取组织培养细胞,
04:28
and infect them with various viruses,
96
268160
2000
用不同的病毒感染它们,
04:30
and we take the stuff and fluorescently label the nucleic acid,
97
270160
4000
用荧光标记核酸,
04:34
the genetic material that comes out of these tissue culture cells --
98
274160
3000
来自这些组织培养细胞的遗传物质——
04:37
mostly viral stuff -- and stick it on the array to see where it sticks.
99
277160
4000
大部分是病毒类的东西——把它粘在芯片上。
04:41
Now, if the DNA sequences match, they'll stick together,
100
281160
2000
如果DNA序列是匹配的,它们就会粘在一起,
04:43
and so we can look at spots.
101
283160
2000
我们来看这些点。
04:45
And if spots light up, we know there's a certain virus in there.
102
285160
2000
如果它们发亮了,我们就知道那有某种病毒。
04:47
That's what one of these chips really looks like,
103
287160
2000
那是其中一张芯片的样子,
04:49
and these red spots are, in fact, signals coming from the virus.
104
289160
3000
这些红点实际上是来自病毒的信号。
04:52
And each spot represents a different family of virus
105
292160
3000
每一个点代表不同的病毒家系
04:55
or species of virus.
106
295160
1000
或者病毒物种。
04:56
And so, that's a hard way to look at things,
107
296160
2000
要看清它们是很困难的,
04:58
so I'm just going to encode things as a little barcode,
108
298160
2000
所以我把它们编成小的条码,
05:00
grouped by family, so you can see the results in a very intuitive way.
109
300160
4000
按家系分组,这样你可以直接看到结果。
05:04
What we did is, we took tissue culture cells
110
304160
2000
我们所做的就是提取组织培养细胞,
05:06
and infected them with adenovirus,
111
306160
2000
用腺病毒感染,
05:08
and you can see this little yellow barcode next to adenovirus.
112
308160
4000
你可以在腺病毒旁边看到这个小的黄色条码。
05:12
And, likewise, we infected them with parainfluenza-3 --
113
312160
3000
同样我们用副流感病毒-3感染———
05:15
that's a paramyxovirus -- and you see a little barcode here.
114
315160
2000
它是副粘病毒——你在这看到小的条码。
05:17
And then we did respiratory syncytial virus.
115
317160
3000
然后我们又用呼吸道合胞病毒。
05:20
That's the scourge of daycare centers everywhere --
116
320160
2000
这是所有日托中心的灾难——
05:22
it's like boogeremia, basically.
117
322160
2000
大体上说就象是鼻粘膜病。
05:24
(Laughter)
118
324160
1000
(笑声)
05:25
You can see that this barcode is the same family,
119
325160
4000
你能看到这个条码是同一家系的,
05:29
but it's distinct from parainfluenza-3,
120
329160
2000
但它与副流感病毒-3不同,
05:31
which gives you a very bad cold.
121
331160
2000
它会使你患非常严重的感冒。
05:33
And so we're getting unique signatures, a fingerprint for each virus.
122
333160
3000
所以我们要有独特的标记,每一种病毒都有一种指纹。
05:36
Polio and rhino: they're in the same family, very close to each other.
123
336160
3000
小儿麻痹症病毒和鼻病毒:它们是同一家系的,相互非常接近。
05:39
Rhino's the common cold, and you all know what polio is,
124
339160
2000
鼻病毒是普通感冒,你们都知道小儿麻痹是什么,
05:41
and you can see that these signatures are distinct.
125
341160
3000
你们可以看到这些标记是不同的。
05:44
And Kaposi's sarcoma-associated herpes virus
126
344160
3000
和卡波济氏肉瘤相关的疱疹病毒
05:47
gives a nice signature down here.
127
347160
2000
底端有很好的标记。
05:49
And so it is not any one stripe or something
128
349160
2000
所以不是一条带或是什么东西
05:51
that tells me I have a virus of a particular type here;
129
351160
2000
来告诉我说这里有一个特殊的病毒;
05:53
it's the barcode that in bulk represents the whole thing.
130
353160
4000
是大量的条码代表整体。
05:57
All right, I can see a rhinovirus --
131
357160
2000
我能看到鼻病毒,
05:59
and here's the blow-up of the rhinovirus's little barcode --
132
359160
2000
这是放大的鼻病毒的小条码,
06:01
but what about different rhinoviruses?
133
361160
2000
那么不同的鼻病毒呢?
06:03
How do I know which rhinovirus I have?
134
363160
2000
我怎么知道我有哪种鼻病毒?
06:05
There're 102 known variants of the common cold,
135
365160
3000
已知普通感冒有102种变异,
06:08
and there're only 102 because people got bored collecting them:
136
368160
3000
仅仅只有102种是因为人们已经厌倦去收集它们了,
06:11
there are just new ones every year.
137
371160
2000
每年都有新的。
06:13
And so, here are four different rhinoviruses,
138
373160
2000
这里有4种不同的鼻病毒,
06:15
and you can see, even with your eye,
139
375160
2000
你可以看到,即使用你的眼睛就可以,
06:17
without any fancy computer pattern-matching
140
377160
2000
而不用任何计算机模式匹配
06:19
recognition software algorithms,
141
379160
2000
识别软件,
06:21
that you can distinguish each one of these barcodes from each other.
142
381160
3000
你就可以区分这些条码。
06:24
Now, this is kind of a cheap shot,
143
384160
2000
这是某种划算的作法,
06:26
because I know what the genetic sequence of all these rhinoviruses is,
144
386160
3000
因为我知道所有这些鼻病毒的遗传序列,
06:29
and I in fact designed the chip
145
389160
1000
并且实际上我设计了芯片
06:30
expressly to be able to tell them apart,
146
390160
2000
能够明确地区分它们,
06:32
but what about rhinoviruses that have never seen a genetic sequencer?
147
392160
4000
但对于还不知道遗传序列的鼻病毒怎么办呢?
06:36
We don't know what the sequence is; just pull them out of the field.
148
396160
2000
我们不知道它的序列,那就不要做它们。
06:38
So, here are four rhinoviruses
149
398160
2000
这是4个鼻病毒
06:40
we never knew anything about --
150
400160
2000
我们对此一无所知,
06:42
no one's ever sequenced them -- and you can also see
151
402160
3000
没有人对它们做过测序,你也能看到
06:45
that you get unique and distinguishable patterns.
152
405160
2000
你得到了独特的且可识别的格局。
06:47
You can imagine building up some library, whether real or virtual,
153
407160
3000
你可以想象建立一个资料室,无论是真实的或是虚拟的,
06:50
of fingerprints of essentially every virus.
154
410160
2000
收藏基本病毒的指纹。
06:52
But that's, again, shooting fish in a barrel, you know, right?
155
412160
3000
但这又是瓮中捉鳖,对吧?
06:55
You have tissue culture cells. There are a ton of viruses.
156
415160
2000
你有组织培养细胞:有大量的病毒。
06:57
What about real people?
157
417160
2000
那么人呢?
06:59
You can't control real people, as you probably know.
158
419160
2000
你控制不了人,就象你所知道的。
07:01
You have no idea what someone's going to cough into a cup,
159
421160
4000
你不知道某个人会往杯子里咳出什么东西,
07:05
and it's probably really complex, right?
160
425160
3000
它可能非常复杂,对不对?
07:08
It could have lots of bacteria, it could have more than one virus,
161
428160
3000
可能有许多细菌,可能有一种以上的病毒,
07:11
and it certainly has host genetic material.
162
431160
2000
它肯定有宿主遗传物质,
07:13
So how do we deal with this?
163
433160
1000
对此我们怎么办?
07:14
And how do we do the positive control here?
164
434160
2000
我们如何做阳性对照?
07:16
Well, it's pretty simple.
165
436160
2000
非常简单。
07:18
That's me, getting a nasal lavage.
166
438160
2000
要是我就做鼻灌洗。
07:20
And the idea is, let's experimentally inoculate people with virus.
167
440160
5000
这个想法就是我们实验性地用病毒给人们接种,
07:25
This is all IRB-approved, by the way; they got paid.
168
445160
5000
这是经人体实验委员会批准的,他们是拿薪水的。
07:30
And basically we experimentally inoculate people
169
450160
3000
简单讲我们用普通感冒病毒
07:33
with the common cold virus.
170
453160
1000
给人接种。
07:34
Or, even better, let's just take people
171
454160
2000
或者更好的是我们把人们
07:36
right out of the emergency room --
172
456160
1000
从急诊室解救出来,
07:37
undefined, community-acquired respiratory tract infections.
173
457160
4000
——未明确的群体获得性呼吸道感染。
07:41
You have no idea what walks in through the door.
174
461160
2000
你不知道什么会从那个门进来,
07:43
So, let's start off with the positive control first,
175
463160
3000
所以让我们以阳性对照开始,
07:46
where we know the person was healthy.
176
466160
2000
我们知道某人是健康的。
07:48
They got a shot of virus up the nose,
177
468160
2000
他们的鼻子受到病毒的袭击,
07:50
let's see what happens.
178
470160
1000
让我们看发生了什么。
07:51
Day zero: nothing happening.
179
471160
2000
当天:什么都没发生。
07:53
They're healthy; they're clean -- it's amazing.
180
473160
2000
他们仍然是健康的,清洁的——很奇怪。
07:55
Actually, we thought the nasal tract might be full of viruses
181
475160
2000
实际上我们认为他们的鼻道会充满病毒,
07:57
even when you're walking around healthy.
182
477160
1000
即使你是在健康人周围走动。
07:58
It's pretty clean. If you're healthy, you're pretty healthy.
183
478160
2000
它相当清洁,如果你是健康的,你是相当健康。
08:00
Day two: we get a very robust rhinovirus pattern,
184
480160
4000
第二天:我们得到了很强的鼻病毒模式,
08:04
and it's very similar to what we get in the lab
185
484160
2000
与我们在实验室做组织培养实验
08:06
doing our tissue culture experiment.
186
486160
1000
得到的非常相似。
08:07
So that's great, but again, cheap shot, right?
187
487160
3000
很好,这又是划算的作法,对吧?
08:10
We put a ton of virus up this guy's nose. So --
188
490160
2000
我们在这个人的鼻子里放大量的病毒,
08:12
(Laughter)
189
492160
1000
(笑声)
08:13
-- I mean, we wanted it to work. He really had a cold.
190
493160
4000
我指,我们希望能这样。他真的感冒了。
08:17
So, how about the people who walk in off the street?
191
497160
4000
走过这条街的人会怎么样?
08:21
Here are two individuals represented by their anonymous ID codes.
192
501160
2000
这里的两个人各自用他们的身份识别码代表,
08:23
They both have rhinoviruses; we've never seen this pattern in lab.
193
503160
4000
他们都有鼻病毒,我们在实验室从未见过这种类型。
08:27
We sequenced part of their viruses;
194
507160
2000
我们做了部分测序,
08:29
they're new rhinoviruses no one's actually even seen.
195
509160
3000
它们是新的鼻病毒,没人见过。
08:32
Remember, our evolutionary-conserved sequences
196
512160
2000
记住,我们在这个芯片上所用的
08:34
we're using on this array allow us to detect
197
514160
2000
进化—保守序列使我们能够检测出
08:36
even novel or uncharacterized viruses,
198
516160
2000
新的或无特征的病毒,
08:38
because we pick what is conserved throughout evolution.
199
518160
4000
因为我们是从整个进化中挑出的保守序列。
08:42
Here's another guy. You can play the diagnosis game yourself here.
200
522160
3000
这是另一个人。你可以自己在这玩诊断游戏。
08:45
These different blocks represent
201
525160
2000
这些不同的块代表
08:47
the different viruses in this paramyxovirus family,
202
527160
2000
副粘病毒系中不同的病毒,
08:49
so you can kind of go down the blocks
203
529160
1000
你可以在这些块下面
08:50
and see where the signal is.
204
530160
2000
看到信号在哪里。
08:52
Well, doesn't have canine distemper; that's probably good.
205
532160
3000
没有犬瘟热,那样可能不错。
08:55
(Laughter)
206
535160
2000
(笑声)
08:57
But by the time you get to block nine,
207
537160
2000
但当你看到第9块时,
08:59
you see that respiratory syncytial virus.
208
539160
2000
你可以看到呼吸合胞病毒。
09:01
Maybe they have kids. And then you can see, also,
209
541160
3000
也许它们有后代了。你也可以看到
09:04
the family member that's related: RSVB is showing up here.
210
544160
2000
与其相关的家系成员:RSVB在这里出现了。
09:06
So, that's great.
211
546160
1000
太好了。
09:07
Here's another individual, sampled on two separate days --
212
547160
3000
这是另外一个人,分2天抽取了血样,
09:10
repeat visits to the clinic.
213
550160
2000
他反复到诊所来。
09:12
This individual has parainfluenza-1,
214
552160
3000
这人有副流感病毒-1,
09:15
and you can see that there's a little stripe over here
215
555160
2000
你能看到这有一条带,
09:17
for Sendai virus: that's mouse parainfluenza.
216
557160
3000
这是仙台病毒:是小鼠副流感病毒。
09:20
The genetic relationships are very close there. That's a lot of fun.
217
560160
4000
有很强的遗传关联,非常有趣。
09:24
So, we built out the chip.
218
564160
1000
因此,我们制作了芯片,
09:25
We made a chip that has every known virus ever discovered on it.
219
565160
4000
芯片上有每一个发现的已知病毒。
09:29
Why not? Every plant virus, every insect virus, every marine virus.
220
569160
3000
每一种植物病毒,每一种昆虫病毒,每一种海产病毒。
09:32
Everything that we could get out of GenBank --
221
572160
2000
我们可以从基因库得到每样东西,
09:34
that is, the national repository of sequences.
222
574160
2000
也就是国家基因序列库。
09:36
Now we're using this chip. And what are we using it for?
223
576160
3000
现在我们来用这个芯片。我们用它做什么?
09:39
Well, first of all, when you have a big chip like this,
224
579160
2000
首先,你有一个大的象这样的芯片,
09:41
you need a little bit more informatics,
225
581160
2000
你需要一些信息,
09:43
so we designed the system to do automatic diagnosis.
226
583160
2000
我们设计的这个系统是自动诊断。
09:45
And the idea is that we simply have virtual patterns,
227
585160
3000
这个想法是我们仅有虚拟模式,
09:48
because we're never going to get samples of every virus --
228
588160
2000
因为我们不可能得到每一个病毒的样本,
09:50
it would be virtually impossible. But we can get virtual patterns,
229
590160
3000
它是完全不可能的。但是我们能得到虚拟模式,
09:53
and compare them to our observed result --
230
593160
2000
将它与我们观察到的结果进行比较,
09:55
which is a very complex mixture -- and come up with some sort of score
231
595160
4000
这是一个非常复杂的混合物,于是我们提出了某种记分法,
09:59
of how likely it is this is a rhinovirus or something.
232
599160
3000
即它是鼻病毒或什么东西的可能性有多大。
10:02
And this is what this looks like.
233
602160
2000
这就是它看起来的样子。
10:04
If, for example, you used a cell culture
234
604160
2000
例如,如果你的细胞培养
10:06
that's chronically infected with papilloma,
235
606160
2000
用乳突病毒慢慢感染,
10:08
you get a little computer readout here,
236
608160
2000
你得到一个计算机读出,
10:10
and our algorithm says it's probably papilloma type 18.
237
610160
4000
我们的算式表示它可能是乳突病毒18型。
10:14
And that is, in fact, what these particular cell cultures
238
614160
2000
实际上培养细胞的病毒就是
10:16
are chronically infected with.
239
616160
2000
慢性感染。
10:18
So let's do something a little bit harder.
240
618160
2000
让我们来做困难点的事吧。
10:20
We put the beeper in the clinic.
241
620160
1000
我们把蜂鸣器放在诊所里。
10:21
When somebody shows up, and the hospital doesn't know what to do
242
621160
3000
病人来了,而医院不知道做什么,
10:24
because they can't diagnose it, they call us.
243
624160
2000
因为医院无法诊断,他们就叫我们。
10:26
That's the idea, and we're setting this up in the Bay Area.
244
626160
2000
就是因为这个,我们在海湾地区装了这个东西。
10:28
And so, this case report happened three weeks ago.
245
628160
2000
这是三周前的一个病例。
10:30
We have a 28-year-old healthy woman, no travel history,
246
630160
3000
一个28岁健康女性,无旅行史,
10:33
[unclear], doesn't smoke, doesn't drink.
247
633160
3000
不抽烟喝酒,
10:36
10-day history of fevers, night sweats, bloody sputum --
248
636160
4000
发烧10天,盗汗,血痰,
10:40
she's coughing up blood -- muscle pain.
249
640160
2000
咳嗽带血,肌肉疼痛。
10:42
She went to the clinic, and they gave her antibiotics
250
642160
4000
她来到诊所,医生给她抗生素,
10:46
and then sent her home.
251
646160
1000
然后送她回家。
10:47
She came back after ten days of fever, right? Still has the fever,
252
647160
4000
10天以后她又来了,仍然发烧,
10:51
and she's hypoxic -- she doesn't have much oxygen in her lungs.
253
651160
3000
她还缺氧——肺部缺氧。
10:54
They did a CT scan.
254
654160
1000
医生给她做了CT扫描。
10:55
A normal lung is all sort of dark and black here.
255
655160
4000
正常的肺这都是暗的和黑的,
10:59
All this white stuff -- it's not good.
256
659160
2000
这些白的东西都不好。
11:01
This sort of tree and bud formation indicates there's inflammation;
257
661160
3000
这种分支和芽胞的形成显示病人有炎症,
11:04
there's likely to be infection.
258
664160
2000
她有可能是感染了。
11:06
OK. So, the patient was treated then
259
666160
3000
因此给病人用
11:09
with a third-generation cephalosporin antibiotic and doxycycline,
260
669160
4000
第三代抗生素头孢菌素和强力霉素进行治疗。
11:13
and on day three, it didn't help: she had progressed to acute failure.
261
673160
4000
第三天,没有任何作用:她发展为急性衰竭。
11:17
They had to intubate her, so they put a tube down her throat
262
677160
3000
医生不得不给她插管,把管子插到她的喉咙里,
11:20
and they began to mechanically ventilate her.
263
680160
1000
开始为她机械换气。
11:21
She could no longer breathe for herself.
264
681160
2000
她不能自主呼吸了。
11:23
What to do next? Don't know.
265
683160
2000
下一步做什么?不知道。
11:25
Switch antibiotics: so they switched to another antibiotic,
266
685160
3000
换抗生素,然后医生就换了另一种抗生素,
11:28
Tamiflu.
267
688160
2000
然后达菲,
11:30
It's not clear why they thought she had the flu,
268
690160
2000
不清楚为什么医生认为她患了感冒,
11:32
but they switched to Tamiflu.
269
692160
2000
但他们改用达菲。
11:34
And on day six, they basically threw in the towel.
270
694160
2000
第六天,他们基本放弃了。
11:36
You do an open lung biopsy when you've got no other options.
271
696160
4000
如果没有别的选择,就是打开肺部做活组织检查。
11:40
There's an eight percent mortality rate with just doing this procedure,
272
700160
2000
做这个的死亡率是8%。
11:42
and so basically -- and what do they learn from it?
273
702160
3000
但从这一步能得到什么?
11:45
You're looking at her open lung biopsy.
274
705160
2000
你看她的肺部组织,
11:47
And I'm no pathologist, but you can't tell much from this.
275
707160
2000
我不是病理学家,但你从这一步也讲不出什么。
11:49
All you can tell is, there's a lot of swelling: bronchiolitis.
276
709160
3000
你能说的也就是有许多肿胀:细支气管炎。
11:52
It was "unrevealing": that's the pathologist's report.
277
712160
3000
它没有结果:这是病理学家的报告。
11:55
And so, what did they test her for?
278
715160
3000
所以,为什么进行这些检测?
11:58
They have their own tests, of course,
279
718160
1000
当然,他们做了许多检测,
11:59
and so they tested her for over 70 different assays,
280
719160
3000
他们为她做了70多项检测,
12:02
for every sort of bacteria and fungus and viral assay
281
722160
3000
对每一种细菌、真菌和病毒都进行了测定。
12:05
you can buy off the shelf:
282
725160
2000
你从这看到的:
12:07
SARS, metapneumovirus, HIV, RSV -- all these.
283
727160
3000
SARS、间质性肺炎病毒、HIV、RSV——所有这些。
12:10
Everything came back negative, over 100,000 dollars worth of tests.
284
730160
4000
结果每项都是阴性。这些检测价值10万美元。
12:14
I mean, they went to the max for this woman.
285
734160
3000
我是指他们为这个妇女尽了最大的努力。
12:17
And basically on hospital day eight, that's when they called us.
286
737160
3000
在医院第8天,他们叫我们去了。
12:20
They gave us endotracheal aspirate --
287
740160
2000
他们给了我们气管内吸取物,
12:22
you know, a little fluid from the throat,
288
742160
2000
你知道,从喉咙取的一点液体,
12:24
from this tube that they got down there -- and they gave us this.
289
744160
2000
从这个管子里,他们下到这个部位。
12:26
We put it on the chip; what do we see? Well, we saw parainfluenza-4.
290
746160
5000
我们把它放在芯片上,我们看到了什么?副流感病毒-4.
12:31
Well, what the hell's parainfluenza-4?
291
751160
2000
副流感病毒-4到底是什么东西?
12:33
No one tests for parainfluenza-4. No one cares about it.
292
753160
3000
没人检测过副流感病毒-4,没人关注它。
12:36
In fact, it's not even really sequenced that much.
293
756160
3000
实际上都没有对它进行过大段测序,
12:39
There's just a little bit of it sequenced.
294
759160
2000
只测了一小段。
12:41
There's almost no epidemiology or studies on it.
295
761160
2000
对它几乎也没有流行病学的研究。
12:43
No one would even consider it,
296
763160
2000
没人考虑过它,
12:45
because no one had a clue that it could cause respiratory failure.
297
765160
3000
因为没人知道它会造成呼吸衰竭。
12:48
And why is that? Just lore. There's no data --
298
768160
3000
为什么会这样?只是传说,没有数据——
12:51
no data to support whether it causes severe or mild disease.
299
771160
4000
没有数据支持它是造成严重的疾患还是轻微疾病。
12:55
Clearly, we have a case of a healthy person that's going down.
300
775160
3000
但清楚的是我们有这样一个病例,一个健康人倒下了。
12:58
OK, that's one case report.
301
778160
3000
这是一例报道。
13:01
I'm going to tell you one last thing in the last two minutes
302
781160
2000
在最后两分钟,我要告诉你们最后一件事情,
13:03
that's unpublished -- it's going to come out tomorrow --
303
783160
3000
还没有公开——明天就会出来——
13:06
and it's an interesting case of how you might use this chip
304
786160
3000
是一个很有趣的例子,你如何用这个芯片
13:09
to find something new and open a new door.
305
789160
2000
发现新的东西,打开一扇新门。
13:11
Prostate cancer. I don't need to give you many statistics
306
791160
4000
前列腺癌。我不需要给你许多关于
13:15
about prostate cancer. Most of you already know it:
307
795160
3000
前列腺癌的统计数据,你们大多对它已经有所了解,
13:18
third leading cause of cancer deaths in the U.S.
308
798160
2000
美国癌症第三大死因。
13:20
Lots of risk factors,
309
800160
2000
它有许多危险因素,
13:22
but there is a genetic predisposition to prostate cancer.
310
802160
4000
其中一个是它的遗传倾向。
13:26
For maybe about 10 percent of prostate cancer,
311
806160
2000
大约10%的前列腺癌患者
13:28
there are folks that are predisposed to it.
312
808160
2000
亲属中有这种倾向。
13:30
And the first gene that was mapped in association studies
313
810160
4000
对早期发作的前列腺癌进行的关联性研究绘制了第一个基因图,
13:34
for this, early-onset prostate cancer, was this gene called RNASEL.
314
814160
4000
这个基因叫做RNASEL。
13:38
What is that? It's an antiviral defense enzyme.
315
818160
3000
它是什么?它是一种抗病毒防御酶。
13:41
So, we're sitting around and thinking,
316
821160
2000
我们坐在一起思考
13:43
"Why would men who have the mutation --
317
823160
2000
为什么有突变的、
13:45
a defect in an antiviral defense system -- get prostate cancer?
318
825160
5000
抗病毒防御系统有缺陷的男人患前列腺癌?
13:50
It doesn't make sense -- unless, maybe, there's a virus?"
319
830160
3000
这没什么意义——除非,也许是有一种病毒。
13:53
So, we put tumors --- and now we have over 100 tumors -- on our array.
320
833160
6000
我们把肿瘤——现在我们有100多种肿瘤——放到芯片上,
13:59
And we know who's got defects in RNASEL and who doesn't.
321
839160
3000
我们知道谁RNASEL有缺陷,谁没有。
14:02
And I'm showing you the signal from the chip here,
322
842160
3000
我给你们看来自芯片的信号,
14:05
and I'm showing you for the block of retroviral oligos.
323
845160
4000
给你们看反转录病毒块。
14:09
And what I'm telling you here from the signal, is
324
849160
2000
从这个信号中我可以告诉你们
14:11
that men who have a mutation in this antiviral defense enzyme,
325
851160
4000
抗病毒防御酶有突变的男人
14:15
and have a tumor, often have -- 40 percent of the time --
326
855160
4000
有肿瘤的机会是40%,
14:19
a signature which reveals a new retrovirus.
327
859160
4000
这个标志显示了一种新的逆转录病毒。
14:23
OK, that's pretty wild. What is it?
328
863160
3000
有点太疯狂了。它是什么?
14:26
So, we clone the whole virus.
329
866160
1000
所以我们克隆了整个病毒。
14:27
First of all, I'll tell you that a little automated prediction told us
330
867160
4000
首先,自动诊断告诉我们
14:31
it was very similar to a mouse virus.
331
871160
2000
它与小鼠病毒非常相似。
14:33
But that doesn't tell us too much,
332
873160
1000
但它没有告诉我们很多,
14:34
so we actually clone the whole thing.
333
874160
2000
所以实际上我们还是克隆了全部。
14:36
And the viral genome I'm showing you right here?
334
876160
2000
我在这里给你们显示这个病毒基因组?
14:38
It's a classic gamma retrovirus, but it's totally new;
335
878160
3000
这是一个典型的伽玛逆转录病毒,是个新的病毒,
14:41
no one's ever seen it before.
336
881160
1000
以前没人见过它。
14:42
Its closest relative is, in fact, from mice,
337
882160
3000
它最近的亲系,实际上是来自小鼠,
14:45
and so we would call this a xenotropic retrovirus,
338
885160
4000
我们把它叫做嗜异性逆转录病毒,
14:49
because it's infecting a species other than mice.
339
889160
3000
它除了感染小鼠,也感染其它物种。
14:52
And this is a little phylogenetic tree
340
892160
2000
这是个树形系统分类
14:54
to see how it's related to other viruses.
341
894160
2000
可以看到它与其它病毒的关系。
14:56
We've done it for many patients now,
342
896160
3000
我们对许多病人都是这样做的,
14:59
and we can say that they're all independent infections.
343
899160
3000
我们认为他们都是独立感染的。
15:02
They all have the same virus,
344
902160
1000
他们都有同一种病毒,
15:03
but they're different enough that there's reason to believe
345
903160
3000
但又有很大的不同,而且有理由相信
15:06
that they've been independently acquired.
346
906160
2000
都是独立获得的。
15:08
Is it really in the tissue? And I'll end up with this: yes.
347
908160
2000
它真的在组织里吗?我将以这个结束我的演讲。是的。
15:10
We take slices of these biopsies of tumor tissue
348
910160
3000
我们利用肿瘤组织切片,
15:13
and use material to actually locate the virus,
349
913160
2000
放置这个病毒,
15:15
and we find cells here with viral particles in them.
350
915160
4000
我们发现细胞里有病毒颗粒,
15:19
These guys really do have this virus.
351
919160
2000
这些人的确都有这个病毒。
15:21
Does this virus cause prostate cancer?
352
921160
2000
这种病毒导致前列腺癌吗?
15:23
Nothing I'm saying here implies causality. I don't know.
353
923160
4000
我在这所说的一切都没有这个因果关系,我不知道。
15:27
Is it a link to oncogenesis? I don't know.
354
927160
2000
它与肿瘤的发生有关吗?我不知道。
15:29
Is it the case that these guys are just more susceptible to viruses?
355
929160
4000
是因为这些人对病毒敏感吗?
15:33
Could be. And it might have nothing to do with cancer.
356
933160
3000
可能是吧。对于癌症它可能什么也做不了,
15:36
But now it's a door.
357
936160
1000
但它是一扇门。
15:37
We have a strong association between the presence of this virus
358
937160
3000
这个病毒与肿瘤遗传变异之间
15:40
and a genetic mutation that's been linked to cancer.
359
940160
3000
有很强的关联。
15:43
That's where we're at.
360
943160
1000
这就是现在我们所知道的。
15:44
So, it opens up more questions than it answers, I'm afraid,
361
944160
4000
所以我想它提出了更多的没有答案的问题,
15:48
but that's what, you know, science is really good at.
362
948160
2000
但这就是科学所在。
15:50
This was all done by folks in the lab --
363
950160
2000
这都是我们实验室做的,
15:52
I cannot take credit for most of this.
364
952160
1000
大多数的成果我都不能居功。
15:53
This is a collaboration between myself and Don.
365
953160
1000
这是我和Don的合作。
15:54
This is the guy who started the project in my lab,
366
954160
3000
这个人在我的实验室开始这个项目,
15:57
and this is the guy who's been doing prostate stuff.
367
957160
2000
这个人是做前列腺研究的。
15:59
Thank you very much. (Applause)
368
959160
3000
非常感谢。
关于本网站

这个网站将向你介绍对学习英语有用的YouTube视频。你将看到来自世界各地的一流教师教授的英语课程。双击每个视频页面上显示的英文字幕,即可从那里播放视频。字幕会随着视频的播放而同步滚动。如果你有任何意见或要求,请使用此联系表与我们联系。

https://forms.gle/WvT1wiN1qDtmnspy7


This website was created in October 2020 and last updated on June 12, 2025.

It is now archived and preserved as an English learning resource.

Some information may be out of date.

隐私政策

eng.lish.video

Developer's Blog