This is a machine transcription and therefore it may contain inaccuracies, errors, or mispronunciations. Notice an error you think needs changing? Please contact the Bitesize Bio team using this form: https://bit.ly/bsbtranscriptions
00:00:07.710 --> 00:00:19.260
Eva Amsen: Hi, and welcome to cryo talk. I'm Eva Anderson, and I'm here today with Peter Shen. Peter is assistant Professor of Biochemistry at the University of Utah. So Hi, Peter, how are you?
3
00:00:19.650 --> 00:00:23.190
Peter Shen: I'm great thanks for asking you, but I'm glad to be here.
4
00:00:23.270 --> 00:00:33.179
Eva Amsen: Yeah, great to have you. Now, the first question that I usually ask people on this podcast is, if you can just maybe tell us a little bit about your career so far.
5
00:00:33.790 --> 00:00:36.309
Peter Shen: Yeah, happy to. So
6
00:00:36.360 --> 00:00:46.879
Peter Shen: I'm an assistant professor here at the University of Utah, and I've started my lab in 2,017. So I've been running my lab for about 5 and a half years now.
7
00:00:46.890 --> 00:00:53.800
Peter Shen: and theme of my lab is that we care about the mechanisms underlying protein on the stasis.
8
00:00:53.900 --> 00:01:13.470
Peter Shen: and this really refers to the balance between how cells make proteins and gets rid of good things that either cells don't need any more, or perhaps problematic proteins that could cause harm to the cell. And so there's a constant balance between how cells make decisions of
9
00:01:14.090 --> 00:01:20.890
Peter Shen: how when to make for things, or how to make proteins, and how to get rid of persons that are no longer needed.
10
00:01:21.200 --> 00:01:30.330
Peter Shen: And so in our lab we have a lot of projects that cover different aspects of of this theme, including
11
00:01:30.390 --> 00:01:33.030
Peter Shen: how proteins are made at the ribosome.
12
00:01:33.180 --> 00:01:42.989
Peter Shen: how proteins become folded, and also the flip side of that equation in terms of how proteins become unfolded prior to their degradation.
13
00:01:44.860 --> 00:02:02.670
Peter Shen: It sounds like it's a. It's very much like the basic principles of biochemistry that you're trying to figure out
14
00:02:02.730 --> 00:02:18.779
Peter Shen: the orchestration of proteins, doing their fulfilling their intended functions, and unsurprisingly, there are many diseases that are associated with proteins not being able to work properly. So this is a theme that
15
00:02:18.950 --> 00:02:24.339
Peter Shen: has attracted me for a long time ever since my post, Doc and
16
00:02:24.450 --> 00:02:28.319
Peter Shen: so excited to be able to run a research program to to be studied.
17
00:02:28.440 --> 00:02:29.599
Eva Amsen: It's very interesting.
18
00:02:30.400 --> 00:02:39.070
Eva Amsen: And and one of the tools you're using is a so how? How are you? using that? And how do you get started with?
19
00:02:40.130 --> 00:02:48.260
Peter Shen: So I answer the second part of that question, how I got started first. I like to say that I was doing cryo yam long before it was
20
00:02:48.370 --> 00:03:02.199
Peter Shen: cool to do it, but I started. I became first exposed to cry again when I was when I just started graduate school at to Brigham young university in 2,006,
21
00:03:02.430 --> 00:03:11.820
Peter Shen: and at the time I'd never heard of the method. certainly, you know, the field wasn't where it is now, in terms of technology or
23
00:03:14.440 --> 00:03:24.660
Peter Shen: all capabilities. And we were fortunate at the time the university had a great microscope 300 kv
24
00:03:24.890 --> 00:03:32.399
Peter Shen: f the itf 30 microscope on site entry holder. And at the time there was
25
00:03:32.530 --> 00:03:52.299
Peter Shen: the lab and ended up joining the lab of David bell map, to to study virus structures. And so at the time was great for studying things that are really big things with a lot of internal symmetry which viruses certainly fit the bill.
26
00:03:52.640 --> 00:04:01.259
Peter Shen: And the reason I got drawn to that is because, you know, I remember the very first time I saw a image, and I just couldn't believe that we could see
27
00:04:02.260 --> 00:04:06.990
Peter Shen: these biological particles with our own eyes.
28
00:04:07.380 --> 00:04:16.430
Peter Shen: you know I I remember the first time seeing a reconstruction, I'm thinking. Oh, is this a simulation? But now these are actual reconstructions generated from your I am images.
29
00:04:16.510 --> 00:04:22.660
Peter Shen: and of course the the field at the time, you know, was very limited in terms of resolution. But that's how
30
00:04:22.690 --> 00:04:23.910
Peter Shen: I became.
31
00:04:23.950 --> 00:04:26.590
Peter Shen: initially exposed to the field.
32
00:04:26.900 --> 00:04:30.530
Peter Shen: And then. you know, over the years.
33
00:04:30.580 --> 00:04:41.769
Peter Shen: I like to think that I've I'm just so lucky to have been in the right place at the right time to have stayed in the field and to have witnessed the amazing technological advances
34
00:04:41.910 --> 00:04:45.759
Peter Shen: and thinking that the best way to answer
35
00:04:45.880 --> 00:05:02.110
Peter Shen: mechanistic questions about biology is to directly visualize them. In fact, in my lab, we have this theme or a model, if you will. Seeing this, believing that there really is no better way to understand biology to be able to directly visualize
36
00:05:02.180 --> 00:05:05.399
Peter Shen: the the protein complexes that we're interested in.
37
00:05:05.550 --> 00:05:16.610
Peter Shen: And so I've come a long ways from studying virus structures to now studying so big complexes, but much smaller than viruses. and through through, probably.
38
00:05:16.880 --> 00:05:30.459
Eva Amsen: Yeah. So have you, have you noticed that over the years? obviously, the technology has changed with you as well. Are you taking advantage of? I guess the technological advances in. I am.
39
00:05:31.040 --> 00:05:34.909
Peter Shen: Yeah, I am. I think you know
40
00:05:35.070 --> 00:05:53.760
Peter Shen: the field is continues to be in a golden age. It's still so exciting to see the advances that continue to be made in terms of hardware advances and software advances where we're not only being able to improve resolution, but also to recover
41
00:05:53.820 --> 00:06:00.769
Peter Shen: multiple confirmational states of a protein of it or a target of interest.
42
00:06:01.020 --> 00:06:13.360
Peter Shen: and so my lab, you know, we we try to stay at the forefront of the technology. just this morning I was playing around with this new tool from shore shears group. that
43
00:06:13.380 --> 00:06:28.219
Peter Shen: as an automated model building feature, where, if you have a good enough. 3D reconstruction. It can automatically build an atomic model for you. And yeah, it's a it's a fascinating tool.
44
00:06:28.340 --> 00:06:36.289
Peter Shen: and so I I think the direction of the field is that you know people are still innovating, and that we're really not
45
00:06:36.610 --> 00:06:43.499
Peter Shen: we're. We're really just scratching the surface in terms of the potential of what we can do with
46
00:06:43.510 --> 00:06:45.459
Peter Shen: image processing.
47
00:06:45.700 --> 00:06:53.349
Eva Amsen: Yeah. Yeah. And I, I love that motto, seeing it's believing. That's it. That's definitely what it's all about with.
48
00:06:53.730 --> 00:07:19.130
Peter Shen: Yeah, I used to add to that. I I mean, I remember my first experiences, you know, doing biochemical experiments as an undergraduate student or in undergraduate labs. And you know, thinking it was really cool, that you know, we could see bands on a gel for proteins and DNA, or you can see a spectral peaks for different spectroscopic techniques. but
49
00:07:19.550 --> 00:07:21.030
Peter Shen: you know, there's always
50
00:07:21.060 --> 00:07:27.509
Peter Shen: it's always satisfying to me to be able to actually see the thing that?
51
00:07:27.820 --> 00:07:40.499
Eva Amsen: yeah, it's a different level. Yeah. And and now you've also been involved with trial. I'm training for example, with the national centers for cryoem. Can you tell us a bit more about that?
52
00:07:40.670 --> 00:07:47.490
Peter Shen: Yeah, I'm happy to. So this so I'm part of
53
00:07:47.870 --> 00:08:00.999
Peter Shen: program that's funded by the Nih that has led to the creation of what we call prior E. M. One on one. And this was created in partnership initially with
54
00:08:01.030 --> 00:08:16.489
Peter Shen: Janet. It was And over the past couple of years we've also extended our expanded our program to also create training for prior electron tomography crowd E. T. 101. And this is in partnership with Julia Rash.
55
00:08:16.760 --> 00:08:20.950
Peter Shen: And so the history of this is that
56
00:08:21.090 --> 00:08:28.660
Peter Shen: in 2,017. This was around the time when the Nih started to put out calls for
57
00:08:28.730 --> 00:08:41.119
Peter Shen: proposals. Grant applications to create curriculum development materials. Recognizing that there is quite an expertise gap in the field where
58
00:08:41.130 --> 00:08:47.810
Peter Shen: There's versioning interest in people wanting to learn from them.
59
00:08:47.990 --> 00:08:53.729
Peter Shen: And again, Nih was ready to fund a national centers
60
00:08:53.830 --> 00:09:01.780
Peter Shen: towards this so-called synchrotron model, such that you know not every institution is going to have their own facility.
61
00:09:01.870 --> 00:09:03.100
Peter Shen: And so
62
00:09:03.410 --> 00:09:13.699
Peter Shen: there, you know, how do we bridge that gap between those who don't have experience doing for them, but want to gain access to national centers?
63
00:09:14.050 --> 00:09:15.210
Peter Shen: And so
64
00:09:15.260 --> 00:09:22.950
Peter Shen: at the time when we applied for this curriculum development. Grant. you know I I don't think that we
65
00:09:22.980 --> 00:09:24.630
Peter Shen: intentionally
66
00:09:24.660 --> 00:09:32.700
Peter Shen: could foresee that we would be working so close to the national centers, but in hindsight, of course, this is what needed to happen.
67
00:09:33.130 --> 00:09:50.380
Peter Shen: And so at the time Janet and I we created. I am 101 which covers the basics of really all practical steps of a priori, and workflow from sample purification and grid preparation all the way to data collection and
68
00:09:50.410 --> 00:09:52.329
Peter Shen: data processing.
69
00:09:52.340 --> 00:10:01.149
Peter Shen: But at the same time these national centers were up and running, you know, multiple high end top of line microscopes at each facility.
70
00:10:01.180 --> 00:10:02.410
Peter Shen: and
71
00:10:03.650 --> 00:10:07.580
Peter Shen: they would also provide their own training courses.
72
00:10:07.910 --> 00:10:25.920
Peter Shen: and we're glad that they're also using a crowd. M. 101 material. But there's still is that skill gap between those who don't have the exposure to driving resources. And you know, how do people know if their Sam was good enough for grabbing them.
73
00:10:26.130 --> 00:10:32.929
Peter Shen: And so it was during the middle of this funding period, where we realized that.
74
00:10:33.010 --> 00:10:39.709
Peter Shen: you know, we need to continue to innovate and develop resources, to to bridge that expertise out.
75
00:10:40.020 --> 00:10:41.250
Peter Shen: And so
76
00:10:41.710 --> 00:10:45.679
Peter Shen: this has now led to the creation of
77
00:10:45.720 --> 00:10:47.799
Peter Shen: what the the national centers
78
00:10:47.810 --> 00:10:51.480
Peter Shen: leading this so called merit badge program.
79
00:10:51.640 --> 00:10:52.680
Peter Shen: where
80
00:10:53.240 --> 00:11:06.450
Peter Shen: students learners can earn specific merit badges that cover a distinct aspect of the crowd in Project workflow. So, for example.
81
00:11:06.590 --> 00:11:09.099
Peter Shen: how do you freeze and create?
82
00:11:09.510 --> 00:11:14.609
Peter Shen: And so this provides some level of certification so that newcomers can.
83
00:11:14.790 --> 00:11:19.759
Peter Shen: It's actually be certified to use these instruments.
84
00:11:19.960 --> 00:11:34.630
Peter Shen: and the spirit of these Mayor badges is then that they're cross honored across the the 3 national centers. Ncat, pn, C. And S. 2 C. 2 at Stanford.
85
00:11:35.300 --> 00:11:51.960
Peter Shen: So I guess that that standardizes the bit. So now they they all have access to the same information. Yeah, that's a great way of putting it. It standardizes the the procedure. And you know, and this is something I think the field needs
86
00:11:51.960 --> 00:12:09.920
Peter Shen: And especially if you have a training. And you know you're gonna put them in front of, you know, an expensive instrument. You know. You want to have a certain level of trust that you know you have them freeze their grid, but that they know what they're doing. So having that certification through a merit badge,
87
00:12:10.070 --> 00:12:13.690
Peter Shen: would would add that confidence?
88
00:12:13.840 --> 00:12:18.450
Peter Shen: And so I I think the spirit of the program is exactly what the field means.
89
00:12:19.600 --> 00:12:26.660
Eva Amsen: And Do you have any insight in Who has used the cry? I am one of one resource since it launched it.
90
00:12:26.770 --> 00:12:29.950
Eva Amsen: How many people? Where are they coming from?
91
00:12:30.440 --> 00:12:40.779
Peter Shen: So we we recently reported this to the Nih. So it's a little bit fresh in my mind. But last I checked, which was a few weeks ago
92
00:12:40.820 --> 00:12:44.919
Peter Shen: we were at about 43,000 unique
93
00:12:44.950 --> 00:13:01.850
Peter Shen: learners worldwide, and about half of them come from the United States. and perhaps not surprisingly the the hotspots of those who are visiting, probably, and when one are using prior 1 one material are those who do have
94
00:13:02.440 --> 00:13:12.760
Peter Shen: existing crowded infrastructure, but probably have a growing base of train. It's a growing base of newcomers who want to know
95
00:13:12.850 --> 00:13:18.530
Peter Shen: the the very basics. And so the way the development.
96
00:13:19.110 --> 00:13:30.290
Peter Shen: groups. I've been structured, I think, has been really nice where we have different levels of expertise and also different groups who cover.
97
00:13:30.560 --> 00:13:32.490
Peter Shen: different
98
00:13:32.660 --> 00:13:47.169
Peter Shen: different aspects of. So, for example, you know, we consider ourselves, you know, really thrive by the one on one level of crowded and one. I just really focus on the basics. But then, if people really want more deeper
99
00:13:47.210 --> 00:13:54.390
Peter Shen: knowledge, then there are grand Jensen's you know, very well known series of
100
00:13:54.490 --> 00:14:04.910
Peter Shen: lecture videos. Fred Sigworth has a series of videos that really takes a deep dive, you know, that's more very advanced crowd em theory.
101
00:14:04.990 --> 00:14:23.879
Peter Shen: and then there are more hands on a curriculum development tools through a using VR tools that are developed by a group that per do. And then, more recently, is group funded to develop more image processing based tools called cryo edu.
102
00:14:23.880 --> 00:14:50.499
Peter Shen: where they do simulations of of image processing results so that people might not necessarily have their own computational resources, can at least go through these simulations and see what happens when they make good or sub optimal decisions and the effects of those distinctions on their outcomes. And so it's been really neat to see how these curriculum developers have come together and offer complementary perspectives.
103
00:14:50.500 --> 00:15:02.569
Peter Shen: And so here, at the with our craven 101, it really does focus on the basics, you know, what does good sample look like? What does a sub optimal sample like, you know? And once
104
00:15:02.600 --> 00:15:08.880
Peter Shen: once these newcomers have established, or at least have some basic understanding of
105
00:15:08.950 --> 00:15:15.380
Peter Shen: calibrating their expectations. Then I think this will save a lot of time and resources in the long run.
106
00:15:15.800 --> 00:15:17.390
Eva Amsen: Yeah, definitely.
107
00:15:17.600 --> 00:15:35.949
Eva Amsen: So from I I guess you also have a little bit of insight in like the the variety of people that use cry oem Do you think that has changed over the years like when you first started where there was, there is typical type of cryoem user. And is that different from what they are now.
108
00:15:38.410 --> 00:15:40.760
Peter Shen: But think a little bit about this question.
109
00:15:40.890 --> 00:15:53.360
Peter Shen: We we do have limited access to this data, because, you know, when we look at our web traffic analytics. It doesn't break down the types of visitors. But
110
00:15:53.930 --> 00:15:58.680
Peter Shen: you know, we do have a way where people can provide feedback
111
00:15:58.910 --> 00:16:11.870
Peter Shen: on course materials, or if they have more specific questions, they have been able to reach out to us specifically over the years. and my sense and I don't have part numbers to back this up. is that
112
00:16:11.980 --> 00:16:15.220
Peter Shen: But my sense is that the general
113
00:16:15.700 --> 00:16:31.629
Peter Shen: proportion of training level has remained pretty consistent over the years in terms of most of the people who reach out to us our early stage graduate students. But there certainly are a lot of faculty members that I've also reached out.
114
00:16:31.870 --> 00:16:40.190
Peter Shen: you know, for example, trained crystallographers who are great biochemist and probably have great samples, but
115
00:16:40.440 --> 00:16:50.549
Peter Shen: haven't had hands on with crowding instrumentation, so those would be faculty members with reached out to us. But I would say, for the most part it's
116
00:16:50.950 --> 00:17:07.270
Peter Shen: early stage graduate students. But the level of our training materials, I would say, even catered to to undergraduates. People are learning about structural biology at a very basic level, where nowadays, I think.
117
00:17:07.440 --> 00:17:11.450
Peter Shen: as I hearken back to my own undergraduate
118
00:17:11.760 --> 00:17:18.069
Peter Shen: experience and learning about, you know, X-ray crystallography, or Nmr, certainly Crow yam was not
119
00:17:18.079 --> 00:17:24.339
Peter Shen: in that mix when I was a student 2020 years ago.
120
00:17:24.650 --> 00:17:32.330
Peter Shen: But now I now, I think probably is probably part of mainstream undergraduate curriculum. And I
121
00:17:33.380 --> 00:17:39.600
Peter Shen: the way that we've assigned them 101 is that they should also cater to that audience as well.
122
00:17:39.680 --> 00:17:48.760
Eva Amsen: And and do you think that having early hands on experience with, I am, can help students find jobs and academic careers.
123
00:17:49.560 --> 00:17:56.530
Peter Shen: Yeah, so one of our motivations, biggest motivations for private M, 101 is that
124
00:17:58.260 --> 00:18:21.899
Peter Shen: you can. someone can read all they want about croem theory. But there really is no substitute for hands on experience. Now that said, we also recognize that that is a limitation of the training tools that we've put it. we've posted on our website because there is really no hands on components. But we to emphasize, you know, through
125
00:18:21.900 --> 00:18:35.419
Peter Shen: the videos that we've posted like walk through videos of, you know, this is how someone handles a side entry holder. This is how someone clips a grid so that they could be loaded into an auto load.
126
00:18:35.440 --> 00:18:42.620
Peter Shen: and so, having those tools available at least helps the learners.
127
00:18:43.580 --> 00:18:44.830
Peter Shen: you come.
128
00:18:45.150 --> 00:19:00.149
Peter Shen: give them a certain level of preparation, so that when they do, when it's time for them to have that hands on experience. It's not a complete foreign experience to them. In fact, I would say that the ideal workflow is that
129
00:19:00.260 --> 00:19:05.140
Peter Shen: a lot of the national centers. They host workshops
130
00:19:05.170 --> 00:19:13.180
Peter Shen: for these purposes, and so, prior to a student attending an in-person hands-on workshop,
131
00:19:13.760 --> 00:19:29.180
Peter Shen: hosted by a national facility, for example, that they would have referred to crowded and one on one materials that maximizes their preparation. again, so that it's not a complete foreign experience for them
132
00:19:29.340 --> 00:19:31.649
Peter Shen: when they do it, but then
133
00:19:31.790 --> 00:19:43.119
Peter Shen: it's in order to be certified, or to have that experience to be marketable for next steps. They? You have to have that hands on experience, and I think there it really is. No substitute for just
134
00:19:43.270 --> 00:19:51.550
Peter Shen: time within a microscope or just muscle memory of how do you freeze grids? Or how do you clip grids?
135
00:19:51.780 --> 00:19:58.049
Peter Shen: the time in front of a computer screen, evaluating what is a good image? What is a bad image?
136
00:19:58.160 --> 00:20:08.269
Peter Shen: And so I think there are multiple layers and it to to gain that expertise. But we're in that crowded one on one is a good starting point for that.
137
00:20:08.760 --> 00:20:19.069
Eva Amsen: And and do you think, that over the years the instruments have become more user, friendly like? Are are there more entry level instruments. Now for people to start using.
138
00:20:20.270 --> 00:20:25.510
Peter Shen: I definitely think that the field has progressed in the right direction in this regard.
139
00:20:25.810 --> 00:20:30.110
Eva Amsen: so does that make it easier for students?
140
00:20:30.140 --> 00:20:33.020
Peter Shen: It it does. And I think,
141
00:20:33.700 --> 00:20:41.720
Peter Shen: I would say, for most in my experience, most students probably don't have as much time
142
00:20:41.780 --> 00:20:45.910
Peter Shen: in front of the microscope or driving on the microscope as
143
00:20:46.170 --> 00:20:48.600
Peter Shen: as they deserve.
144
00:20:48.740 --> 00:21:04.150
Peter Shen: And you know, depending on the facility. For example, it's understandable if you know, if you don't want to trust complete newbies to to fiddle around with your multi 1 million dollar instruments. But
145
00:21:04.160 --> 00:21:15.989
Peter Shen: along those lines, though it's the level of involvement to. For example, align. A microscope has been greatly simplified even to the point of automated
146
00:21:16.040 --> 00:21:20.450
Peter Shen: compared to, you know, 10 plus years ago.
147
00:21:20.760 --> 00:21:21.850
Peter Shen: And so
148
00:21:22.490 --> 00:21:28.950
Peter Shen: I would say that a lot of the skills that I learned as a training are probably considered antiquated, you know in terms of
149
00:21:29.040 --> 00:21:33.880
Peter Shen: you know, aligning a side entry microscope
150
00:21:33.960 --> 00:21:37.710
Peter Shen: or even operating a side entry holder. I think
151
00:21:37.850 --> 00:21:52.029
Peter Shen: you know the fewer and fewer institutions are supporting those types of instruments. And you know, seeing the new microscopes that are coming out, where, for example, you have dedicated screening microscopes that are pretty automated.
152
00:21:52.100 --> 00:21:56.020
Peter Shen: And so I think the level of
153
00:21:57.040 --> 00:22:03.349
Peter Shen: maybe not necessarily the level of expertise. But the the focal point of the expertise have shifted
154
00:22:03.420 --> 00:22:05.229
Peter Shen: hopefully here. It's where.
155
00:22:05.640 --> 00:22:18.370
Peter Shen: you know. I don't know how many hours I've spent in, for example, developing film you know,
156
00:22:18.490 --> 00:22:24.910
Peter Shen: And so for my own training, I'm I'm sensitive to this when, as I'm bringing in new graduate students and post docs that
157
00:22:24.920 --> 00:22:32.159
Peter Shen: I'm thinking about, you know. Is it really worth your time, you know. Would it make you more marketable if you
158
00:22:32.320 --> 00:22:35.750
Peter Shen: if you had these skills and
159
00:22:35.950 --> 00:22:49.269
Peter Shen: maybe less so, and I would rather have them spend their time on on using state of the art instrumentation so that they can focus more on their own objects rather than the technical expertise
160
00:22:49.600 --> 00:22:51.800
Eva Amsen: that makes sense. Yeah, thanks.
161
00:22:52.180 --> 00:23:04.630
Eva Amsen: I want to change directions slightly and ask you, So we've talked a lot about. But we can cry, I am. But what do you like to do when you're not working? Do you have any hobbies or
162
00:23:04.740 --> 00:23:08.340
Peter Shen: hobbies? Some things that come to mind
163
00:23:08.850 --> 00:23:29.640
Peter Shen: I like playing basketball and so our department, we have a a weekly series of pick up basketball that's led by graduate students and post docs, and they've been generous enough to let that old faculty members like myself join them up with them. But
164
00:23:29.980 --> 00:23:31.969
Peter Shen: That that is one hobby.
165
00:23:32.240 --> 00:23:39.789
Peter Shen: I'm at a stage of my life where a lot of my time is focused on the 3 kids that that I have
166
00:23:39.970 --> 00:23:51.099
Peter Shen: ranging from elementary to to middle school. And you know, that comes with a lot of time spent on sports and music lessons.
167
00:23:51.250 --> 00:23:56.090
Peter Shen: but turning that into also a hobby where I'm
168
00:23:56.270 --> 00:23:59.959
Peter Shen: practicing sports with all we're playing music with them
169
00:24:00.210 --> 00:24:05.820
Peter Shen: And then just over the and I would say
170
00:24:05.860 --> 00:24:26.110
Peter Shen: another hobby that comes to mind something that we've picked up over the past few years is, really enjoying the great outdoors here in the top. Just have so much access to to beautiful wilderness, including 5 national parts. In fact, just this past weekend. Now, we spent the weekend down at a national park, and
171
00:24:26.110 --> 00:24:43.009
Eva Amsen: got to get away from the city for a little bit
172
00:24:43.010 --> 00:24:56.110
Peter Shen: travel to to go outdoors. You know I didn't go to my first national park until about 5 years ago. I spent most of my life here in Utah.
173
00:24:56.150 --> 00:25:17.219
Peter Shen: but I certainly didn't take advantage of of the beauty that we have here until most recently, and that was part spurred by. you know, kids getting older and just leading to find more bonding activities. And, boy, I just think about how much I've missed out on not taking advantage of that sooner.
174
00:25:17.560 --> 00:25:18.500
Eva Amsen: Yeah.
175
00:25:18.790 --> 00:25:27.529
Eva Amsen: And and and when you were indoors, do you? Do you have any like things like, do you like reading or films or music.
176
00:25:27.860 --> 00:25:32.210
Eva Amsen: any recommendations, perhaps, for our listeners.
177
00:25:32.260 --> 00:25:36.559
Peter Shen: When I'm indoors
178
00:25:37.490 --> 00:25:51.219
Peter Shen: we at home we play a lot of board games. it's fun where you know the the the kids are at the point where we can play more strategy based games. So we definitely
179
00:25:51.460 --> 00:25:56.260
Peter Shen: it depends on who you're with, I would say, if you're with
180
00:25:56.350 --> 00:26:03.110
Peter Shen: a bigger group, and you like chaos One game that we love is called Captain Sonar.
181
00:26:03.280 --> 00:26:32.299
Peter Shen: I don't know if you've heard of it, but it think of it as a battleship on steroids where you have 2 teams that is in charge of navigating a submarine, but trying to blow up the other submarine. And so the 2 teams are sitting on opposite sides of the table, and things are happening in real time. And so people are talking over one another, and you're trying to eavesdrop and keep track on what the other team is doing. And so that's that's a lot of fun.
182
00:26:32.310 --> 00:26:42.969
Peter Shen: now, we we like a lot of puzzle based games. you know, mixing, mixing, and matching certain tiles. So the game a zoom comes to mind.
183
00:26:43.290 --> 00:27:07.139
Peter Shen: Another party game that we go to again that we like is called code names. But anyway, there, there's so many. So I think if you open our closet at home, there's more than 100 games, and some of them are probably still shrinker at. So that's something that our family definitely enjoys indoors. So the other thing is that we're
184
00:27:07.340 --> 00:27:21.470
Peter Shen: We like music. And so I play the piano. My wife plays the cello and our kids play different instruments. We have someone learning the viola
185
00:27:21.700 --> 00:27:27.740
Peter Shen: something for the violin, and so like find songs where we can
186
00:27:27.880 --> 00:27:54.099
Eva Amsen: play with each other or a company. yeah, that's great. I I actually play violin myself. So I love hearing that. And your kid that's learning via life is going to have a lot of options, because all the orchestras are always short of vonless. That was a little bit of a tactical decision when you think about what instrument you wanted to pick up. And so yeah, he's enjoying it. Yeah, that's great.
187
00:27:54.390 --> 00:28:03.089
Eva Amsen: Another question that I love asking people is, if you were not a scientist, what would you be? What would you do? Have you ever thought of that?
188
00:28:03.890 --> 00:28:05.539
Peter Shen: Certainly thought about it.
189
00:28:06.050 --> 00:28:19.580
Peter Shen: I think, probably in a practical sense. I come from a family of lawyers. and it's actually something that's career track that I considered
190
00:28:19.720 --> 00:28:24.720
Peter Shen: after graduate school, something that I considered, you know, in the middle of my post. Stop!
191
00:28:24.860 --> 00:28:33.439
Peter Shen: I don't think I would have been very good at it but my in a practical option. But in terms of
192
00:28:33.800 --> 00:28:39.859
Peter Shen: things that would be more fun. I thought about
193
00:28:39.940 --> 00:28:44.450
Peter Shen: food trucks something about
194
00:28:44.510 --> 00:28:54.070
Peter Shen: operating a mobile kitchen that has always drawn to me and some of my favorite food as ours is from food trucks. And so
195
00:28:54.220 --> 00:29:05.609
Peter Shen: yeah, when I was a boy. I wanted to be a pizza delivery driver, so you can tell that I'm I'm I'm drawn to food.
196
00:29:05.860 --> 00:29:12.310
Peter Shen: well, I like. So after just saying that I would operate the truck.
197
00:29:12.700 --> 00:29:23.790
Peter Shen: I would say I'm very privileged to have very talented wife who cooks very well.
198
00:29:24.070 --> 00:29:29.330
Peter Shen: And she, you know, explores different cuisines. And so I've definitely benefited from that.
199
00:29:29.410 --> 00:29:48.799
Peter Shen: I really like to make sushi something we do on a pretty regular basis. and so but that that might be the extent of my culinary school. Well, that's pretty difficult. I can never get the rules to stay together. So the rice having a really good rice. Now.
200
00:29:49.520 --> 00:29:52.300
Eva Amsen: thanks for that tip. Gonna try it again now.
201
00:29:52.720 --> 00:30:10.359
Eva Amsen: And the last thing I wanted to ask you is we always ask for guests for a little piece of advice, and I think with your experience in cry way, I'm training Is there any piece of advice that you would give students who are interested in a career that involves.
202
00:30:14.760 --> 00:30:19.879
Peter Shen: I would say, the first thing that comes to mind with that question is something that I tell
203
00:30:19.970 --> 00:30:23.320
Peter Shen: everyone who's interested in joining my lab
204
00:30:23.500 --> 00:30:25.309
Peter Shen: is that
205
00:30:25.390 --> 00:30:31.100
Peter Shen: you know, as long as they're surrounded it in this environment is to ask questions.
206
00:30:31.240 --> 00:30:32.250
Peter Shen: Oh.
207
00:30:32.870 --> 00:30:36.549
Peter Shen: in my experience that's always been the fastest way to learn.
208
00:30:36.830 --> 00:30:48.609
Peter Shen: And I would say, it's even more important. So now Because my my sense is that you know we we have moved into a more
209
00:30:48.820 --> 00:31:03.329
Peter Shen: isolated mindset. naturally, because of the pandemic and the merging out of the we've gotten used to isolation and gotten used to trying to figure things out on our own. I think to an extent we have to do that we have to do our own due diligence.
210
00:31:03.460 --> 00:31:05.370
Peter Shen: but
211
00:31:05.740 --> 00:31:11.029
Peter Shen: for trainees out there who have the benefit of being surrounded by expertise.
212
00:31:11.040 --> 00:31:12.520
Peter Shen: Ask questions
213
00:31:12.530 --> 00:31:17.389
Peter Shen: I love it when people can just walk into my office and just wanna on the chat.
214
00:31:17.610 --> 00:31:25.149
Peter Shen: I love it when people drop me cold call emails, you know, after browsing crowded, and one on one and wanting to learn more.
215
00:31:25.270 --> 00:31:30.700
Peter Shen: And I always make it a point to to respond, to to call call emails
216
00:31:30.930 --> 00:31:37.820
Peter Shen: So that that's the first thing that comes to mind is to ask.
217
00:31:38.910 --> 00:31:59.970
Eva Amsen: That's great advice. And yeah, I think that's a that's also a good thing to close on after I asked you so many questions, and you've encouraged people to ask more questions. I think that brings us to the end of our episode today. So thank you very much, Peter, for being our guest today, and thanks everyone else for listening to or watching, cry out, talk.
00:00:07.710 --> 00:00:19.260
Eva Amsen: Hi, and welcome to cryo talk. I'm Eva Anderson, and I'm here today with Peter Shen. Peter is assistant Professor of Biochemistry at the University of Utah. So Hi, Peter, how are you?
3
00:00:19.650 --> 00:00:23.190
Peter Shen: I'm great thanks for asking you, but I'm glad to be here.
4
00:00:23.270 --> 00:00:33.179
Eva Amsen: Yeah, great to have you. Now, the first question that I usually ask people on this podcast is, if you can just maybe tell us a little bit about your career so far.
5
00:00:33.790 --> 00:00:36.309
Peter Shen: Yeah, happy to. So
6
00:00:36.360 --> 00:00:46.879
Peter Shen: I'm an assistant professor here at the University of Utah, and I've started my lab in 2,017. So I've been running my lab for about 5 and a half years now.
7
00:00:46.890 --> 00:00:53.800
Peter Shen: and theme of my lab is that we care about the mechanisms underlying protein on the stasis.
8
00:00:53.900 --> 00:01:13.470
Peter Shen: and this really refers to the balance between how cells make proteins and gets rid of good things that either cells don't need any more, or perhaps problematic proteins that could cause harm to the cell. And so there's a constant balance between how cells make decisions of
9
00:01:14.090 --> 00:01:20.890
Peter Shen: how when to make for things, or how to make proteins, and how to get rid of persons that are no longer needed.
10
00:01:21.200 --> 00:01:30.330
Peter Shen: And so in our lab we have a lot of projects that cover different aspects of of this theme, including
11
00:01:30.390 --> 00:01:33.030
Peter Shen: how proteins are made at the ribosome.
12
00:01:33.180 --> 00:01:42.989
Peter Shen: how proteins become folded, and also the flip side of that equation in terms of how proteins become unfolded prior to their degradation.
13
00:01:44.860 --> 00:02:02.670
Peter Shen: It sounds like it's a. It's very much like the basic principles of biochemistry that you're trying to figure out
14
00:02:02.730 --> 00:02:18.779
Peter Shen: the orchestration of proteins, doing their fulfilling their intended functions, and unsurprisingly, there are many diseases that are associated with proteins not being able to work properly. So this is a theme that
15
00:02:18.950 --> 00:02:24.339
Peter Shen: has attracted me for a long time ever since my post, Doc and
16
00:02:24.450 --> 00:02:28.319
Peter Shen: so excited to be able to run a research program to to be studied.
17
00:02:28.440 --> 00:02:29.599
Eva Amsen: It's very interesting.
18
00:02:30.400 --> 00:02:39.070
Eva Amsen: And and one of the tools you're using is a so how? How are you? using that? And how do you get started with?
19
00:02:40.130 --> 00:02:48.260
Peter Shen: So I answer the second part of that question, how I got started first. I like to say that I was doing cryo yam long before it was
20
00:02:48.370 --> 00:03:02.199
Peter Shen: cool to do it, but I started. I became first exposed to cry again when I was when I just started graduate school at to Brigham young university in 2,006,
21
00:03:02.430 --> 00:03:11.820
Peter Shen: and at the time I'd never heard of the method. certainly, you know, the field wasn't where it is now, in terms of technology or
23
00:03:14.440 --> 00:03:24.660
Peter Shen: all capabilities. And we were fortunate at the time the university had a great microscope 300 kv
24
00:03:24.890 --> 00:03:32.399
Peter Shen: f the itf 30 microscope on site entry holder. And at the time there was
25
00:03:32.530 --> 00:03:52.299
Peter Shen: the lab and ended up joining the lab of David bell map, to to study virus structures. And so at the time was great for studying things that are really big things with a lot of internal symmetry which viruses certainly fit the bill.
26
00:03:52.640 --> 00:04:01.259
Peter Shen: And the reason I got drawn to that is because, you know, I remember the very first time I saw a image, and I just couldn't believe that we could see
27
00:04:02.260 --> 00:04:06.990
Peter Shen: these biological particles with our own eyes.
28
00:04:07.380 --> 00:04:16.430
Peter Shen: you know I I remember the first time seeing a reconstruction, I'm thinking. Oh, is this a simulation? But now these are actual reconstructions generated from your I am images.
29
00:04:16.510 --> 00:04:22.660
Peter Shen: and of course the the field at the time, you know, was very limited in terms of resolution. But that's how
30
00:04:22.690 --> 00:04:23.910
Peter Shen: I became.
31
00:04:23.950 --> 00:04:26.590
Peter Shen: initially exposed to the field.
32
00:04:26.900 --> 00:04:30.530
Peter Shen: And then. you know, over the years.
33
00:04:30.580 --> 00:04:41.769
Peter Shen: I like to think that I've I'm just so lucky to have been in the right place at the right time to have stayed in the field and to have witnessed the amazing technological advances
34
00:04:41.910 --> 00:04:45.759
Peter Shen: and thinking that the best way to answer
35
00:04:45.880 --> 00:05:02.110
Peter Shen: mechanistic questions about biology is to directly visualize them. In fact, in my lab, we have this theme or a model, if you will. Seeing this, believing that there really is no better way to understand biology to be able to directly visualize
36
00:05:02.180 --> 00:05:05.399
Peter Shen: the the protein complexes that we're interested in.
37
00:05:05.550 --> 00:05:16.610
Peter Shen: And so I've come a long ways from studying virus structures to now studying so big complexes, but much smaller than viruses. and through through, probably.
38
00:05:16.880 --> 00:05:30.459
Eva Amsen: Yeah. So have you, have you noticed that over the years? obviously, the technology has changed with you as well. Are you taking advantage of? I guess the technological advances in. I am.
39
00:05:31.040 --> 00:05:34.909
Peter Shen: Yeah, I am. I think you know
40
00:05:35.070 --> 00:05:53.760
Peter Shen: the field is continues to be in a golden age. It's still so exciting to see the advances that continue to be made in terms of hardware advances and software advances where we're not only being able to improve resolution, but also to recover
41
00:05:53.820 --> 00:06:00.769
Peter Shen: multiple confirmational states of a protein of it or a target of interest.
42
00:06:01.020 --> 00:06:13.360
Peter Shen: and so my lab, you know, we we try to stay at the forefront of the technology. just this morning I was playing around with this new tool from shore shears group. that
43
00:06:13.380 --> 00:06:28.219
Peter Shen: as an automated model building feature, where, if you have a good enough. 3D reconstruction. It can automatically build an atomic model for you. And yeah, it's a it's a fascinating tool.
44
00:06:28.340 --> 00:06:36.289
Peter Shen: and so I I think the direction of the field is that you know people are still innovating, and that we're really not
45
00:06:36.610 --> 00:06:43.499
Peter Shen: we're. We're really just scratching the surface in terms of the potential of what we can do with
46
00:06:43.510 --> 00:06:45.459
Peter Shen: image processing.
47
00:06:45.700 --> 00:06:53.349
Eva Amsen: Yeah. Yeah. And I, I love that motto, seeing it's believing. That's it. That's definitely what it's all about with.
48
00:06:53.730 --> 00:07:19.130
Peter Shen: Yeah, I used to add to that. I I mean, I remember my first experiences, you know, doing biochemical experiments as an undergraduate student or in undergraduate labs. And you know, thinking it was really cool, that you know, we could see bands on a gel for proteins and DNA, or you can see a spectral peaks for different spectroscopic techniques. but
49
00:07:19.550 --> 00:07:21.030
Peter Shen: you know, there's always
50
00:07:21.060 --> 00:07:27.509
Peter Shen: it's always satisfying to me to be able to actually see the thing that?
51
00:07:27.820 --> 00:07:40.499
Eva Amsen: yeah, it's a different level. Yeah. And and now you've also been involved with trial. I'm training for example, with the national centers for cryoem. Can you tell us a bit more about that?
52
00:07:40.670 --> 00:07:47.490
Peter Shen: Yeah, I'm happy to. So this so I'm part of
53
00:07:47.870 --> 00:08:00.999
Peter Shen: program that's funded by the Nih that has led to the creation of what we call prior E. M. One on one. And this was created in partnership initially with
54
00:08:01.030 --> 00:08:16.489
Peter Shen: Janet. It was And over the past couple of years we've also extended our expanded our program to also create training for prior electron tomography crowd E. T. 101. And this is in partnership with Julia Rash.
55
00:08:16.760 --> 00:08:20.950
Peter Shen: And so the history of this is that
56
00:08:21.090 --> 00:08:28.660
Peter Shen: in 2,017. This was around the time when the Nih started to put out calls for
57
00:08:28.730 --> 00:08:41.119
Peter Shen: proposals. Grant applications to create curriculum development materials. Recognizing that there is quite an expertise gap in the field where
58
00:08:41.130 --> 00:08:47.810
Peter Shen: There's versioning interest in people wanting to learn from them.
59
00:08:47.990 --> 00:08:53.729
Peter Shen: And again, Nih was ready to fund a national centers
60
00:08:53.830 --> 00:09:01.780
Peter Shen: towards this so-called synchrotron model, such that you know not every institution is going to have their own facility.
61
00:09:01.870 --> 00:09:03.100
Peter Shen: And so
62
00:09:03.410 --> 00:09:13.699
Peter Shen: there, you know, how do we bridge that gap between those who don't have experience doing for them, but want to gain access to national centers?
63
00:09:14.050 --> 00:09:15.210
Peter Shen: And so
64
00:09:15.260 --> 00:09:22.950
Peter Shen: at the time when we applied for this curriculum development. Grant. you know I I don't think that we
65
00:09:22.980 --> 00:09:24.630
Peter Shen: intentionally
66
00:09:24.660 --> 00:09:32.700
Peter Shen: could foresee that we would be working so close to the national centers, but in hindsight, of course, this is what needed to happen.
67
00:09:33.130 --> 00:09:50.380
Peter Shen: And so at the time Janet and I we created. I am 101 which covers the basics of really all practical steps of a priori, and workflow from sample purification and grid preparation all the way to data collection and
68
00:09:50.410 --> 00:09:52.329
Peter Shen: data processing.
69
00:09:52.340 --> 00:10:01.149
Peter Shen: But at the same time these national centers were up and running, you know, multiple high end top of line microscopes at each facility.
70
00:10:01.180 --> 00:10:02.410
Peter Shen: and
71
00:10:03.650 --> 00:10:07.580
Peter Shen: they would also provide their own training courses.
72
00:10:07.910 --> 00:10:25.920
Peter Shen: and we're glad that they're also using a crowd. M. 101 material. But there's still is that skill gap between those who don't have the exposure to driving resources. And you know, how do people know if their Sam was good enough for grabbing them.
73
00:10:26.130 --> 00:10:32.929
Peter Shen: And so it was during the middle of this funding period, where we realized that.
74
00:10:33.010 --> 00:10:39.709
Peter Shen: you know, we need to continue to innovate and develop resources, to to bridge that expertise out.
75
00:10:40.020 --> 00:10:41.250
Peter Shen: And so
76
00:10:41.710 --> 00:10:45.679
Peter Shen: this has now led to the creation of
77
00:10:45.720 --> 00:10:47.799
Peter Shen: what the the national centers
78
00:10:47.810 --> 00:10:51.480
Peter Shen: leading this so called merit badge program.
79
00:10:51.640 --> 00:10:52.680
Peter Shen: where
80
00:10:53.240 --> 00:11:06.450
Peter Shen: students learners can earn specific merit badges that cover a distinct aspect of the crowd in Project workflow. So, for example.
81
00:11:06.590 --> 00:11:09.099
Peter Shen: how do you freeze and create?
82
00:11:09.510 --> 00:11:14.609
Peter Shen: And so this provides some level of certification so that newcomers can.
83
00:11:14.790 --> 00:11:19.759
Peter Shen: It's actually be certified to use these instruments.
84
00:11:19.960 --> 00:11:34.630
Peter Shen: and the spirit of these Mayor badges is then that they're cross honored across the the 3 national centers. Ncat, pn, C. And S. 2 C. 2 at Stanford.
85
00:11:35.300 --> 00:11:51.960
Peter Shen: So I guess that that standardizes the bit. So now they they all have access to the same information. Yeah, that's a great way of putting it. It standardizes the the procedure. And you know, and this is something I think the field needs
86
00:11:51.960 --> 00:12:09.920
Peter Shen: And especially if you have a training. And you know you're gonna put them in front of, you know, an expensive instrument. You know. You want to have a certain level of trust that you know you have them freeze their grid, but that they know what they're doing. So having that certification through a merit badge,
87
00:12:10.070 --> 00:12:13.690
Peter Shen: would would add that confidence?
88
00:12:13.840 --> 00:12:18.450
Peter Shen: And so I I think the spirit of the program is exactly what the field means.
89
00:12:19.600 --> 00:12:26.660
Eva Amsen: And Do you have any insight in Who has used the cry? I am one of one resource since it launched it.
90
00:12:26.770 --> 00:12:29.950
Eva Amsen: How many people? Where are they coming from?
91
00:12:30.440 --> 00:12:40.779
Peter Shen: So we we recently reported this to the Nih. So it's a little bit fresh in my mind. But last I checked, which was a few weeks ago
92
00:12:40.820 --> 00:12:44.919
Peter Shen: we were at about 43,000 unique
93
00:12:44.950 --> 00:13:01.850
Peter Shen: learners worldwide, and about half of them come from the United States. and perhaps not surprisingly the the hotspots of those who are visiting, probably, and when one are using prior 1 one material are those who do have
94
00:13:02.440 --> 00:13:12.760
Peter Shen: existing crowded infrastructure, but probably have a growing base of train. It's a growing base of newcomers who want to know
95
00:13:12.850 --> 00:13:18.530
Peter Shen: the the very basics. And so the way the development.
96
00:13:19.110 --> 00:13:30.290
Peter Shen: groups. I've been structured, I think, has been really nice where we have different levels of expertise and also different groups who cover.
97
00:13:30.560 --> 00:13:32.490
Peter Shen: different
98
00:13:32.660 --> 00:13:47.169
Peter Shen: different aspects of. So, for example, you know, we consider ourselves, you know, really thrive by the one on one level of crowded and one. I just really focus on the basics. But then, if people really want more deeper
99
00:13:47.210 --> 00:13:54.390
Peter Shen: knowledge, then there are grand Jensen's you know, very well known series of
100
00:13:54.490 --> 00:14:04.910
Peter Shen: lecture videos. Fred Sigworth has a series of videos that really takes a deep dive, you know, that's more very advanced crowd em theory.
101
00:14:04.990 --> 00:14:23.879
Peter Shen: and then there are more hands on a curriculum development tools through a using VR tools that are developed by a group that per do. And then, more recently, is group funded to develop more image processing based tools called cryo edu.
102
00:14:23.880 --> 00:14:50.499
Peter Shen: where they do simulations of of image processing results so that people might not necessarily have their own computational resources, can at least go through these simulations and see what happens when they make good or sub optimal decisions and the effects of those distinctions on their outcomes. And so it's been really neat to see how these curriculum developers have come together and offer complementary perspectives.
103
00:14:50.500 --> 00:15:02.569
Peter Shen: And so here, at the with our craven 101, it really does focus on the basics, you know, what does good sample look like? What does a sub optimal sample like, you know? And once
104
00:15:02.600 --> 00:15:08.880
Peter Shen: once these newcomers have established, or at least have some basic understanding of
105
00:15:08.950 --> 00:15:15.380
Peter Shen: calibrating their expectations. Then I think this will save a lot of time and resources in the long run.
106
00:15:15.800 --> 00:15:17.390
Eva Amsen: Yeah, definitely.
107
00:15:17.600 --> 00:15:35.949
Eva Amsen: So from I I guess you also have a little bit of insight in like the the variety of people that use cry oem Do you think that has changed over the years like when you first started where there was, there is typical type of cryoem user. And is that different from what they are now.
108
00:15:38.410 --> 00:15:40.760
Peter Shen: But think a little bit about this question.
109
00:15:40.890 --> 00:15:53.360
Peter Shen: We we do have limited access to this data, because, you know, when we look at our web traffic analytics. It doesn't break down the types of visitors. But
110
00:15:53.930 --> 00:15:58.680
Peter Shen: you know, we do have a way where people can provide feedback
111
00:15:58.910 --> 00:16:11.870
Peter Shen: on course materials, or if they have more specific questions, they have been able to reach out to us specifically over the years. and my sense and I don't have part numbers to back this up. is that
112
00:16:11.980 --> 00:16:15.220
Peter Shen: But my sense is that the general
113
00:16:15.700 --> 00:16:31.629
Peter Shen: proportion of training level has remained pretty consistent over the years in terms of most of the people who reach out to us our early stage graduate students. But there certainly are a lot of faculty members that I've also reached out.
114
00:16:31.870 --> 00:16:40.190
Peter Shen: you know, for example, trained crystallographers who are great biochemist and probably have great samples, but
115
00:16:40.440 --> 00:16:50.549
Peter Shen: haven't had hands on with crowding instrumentation, so those would be faculty members with reached out to us. But I would say, for the most part it's
116
00:16:50.950 --> 00:17:07.270
Peter Shen: early stage graduate students. But the level of our training materials, I would say, even catered to to undergraduates. People are learning about structural biology at a very basic level, where nowadays, I think.
117
00:17:07.440 --> 00:17:11.450
Peter Shen: as I hearken back to my own undergraduate
118
00:17:11.760 --> 00:17:18.069
Peter Shen: experience and learning about, you know, X-ray crystallography, or Nmr, certainly Crow yam was not
119
00:17:18.079 --> 00:17:24.339
Peter Shen: in that mix when I was a student 2020 years ago.
120
00:17:24.650 --> 00:17:32.330
Peter Shen: But now I now, I think probably is probably part of mainstream undergraduate curriculum. And I
121
00:17:33.380 --> 00:17:39.600
Peter Shen: the way that we've assigned them 101 is that they should also cater to that audience as well.
122
00:17:39.680 --> 00:17:48.760
Eva Amsen: And and do you think that having early hands on experience with, I am, can help students find jobs and academic careers.
123
00:17:49.560 --> 00:17:56.530
Peter Shen: Yeah, so one of our motivations, biggest motivations for private M, 101 is that
124
00:17:58.260 --> 00:18:21.899
Peter Shen: you can. someone can read all they want about croem theory. But there really is no substitute for hands on experience. Now that said, we also recognize that that is a limitation of the training tools that we've put it. we've posted on our website because there is really no hands on components. But we to emphasize, you know, through
125
00:18:21.900 --> 00:18:35.419
Peter Shen: the videos that we've posted like walk through videos of, you know, this is how someone handles a side entry holder. This is how someone clips a grid so that they could be loaded into an auto load.
126
00:18:35.440 --> 00:18:42.620
Peter Shen: and so, having those tools available at least helps the learners.
127
00:18:43.580 --> 00:18:44.830
Peter Shen: you come.
128
00:18:45.150 --> 00:19:00.149
Peter Shen: give them a certain level of preparation, so that when they do, when it's time for them to have that hands on experience. It's not a complete foreign experience to them. In fact, I would say that the ideal workflow is that
129
00:19:00.260 --> 00:19:05.140
Peter Shen: a lot of the national centers. They host workshops
130
00:19:05.170 --> 00:19:13.180
Peter Shen: for these purposes, and so, prior to a student attending an in-person hands-on workshop,
131
00:19:13.760 --> 00:19:29.180
Peter Shen: hosted by a national facility, for example, that they would have referred to crowded and one on one materials that maximizes their preparation. again, so that it's not a complete foreign experience for them
132
00:19:29.340 --> 00:19:31.649
Peter Shen: when they do it, but then
133
00:19:31.790 --> 00:19:43.119
Peter Shen: it's in order to be certified, or to have that experience to be marketable for next steps. They? You have to have that hands on experience, and I think there it really is. No substitute for just
134
00:19:43.270 --> 00:19:51.550
Peter Shen: time within a microscope or just muscle memory of how do you freeze grids? Or how do you clip grids?
135
00:19:51.780 --> 00:19:58.049
Peter Shen: the time in front of a computer screen, evaluating what is a good image? What is a bad image?
136
00:19:58.160 --> 00:20:08.269
Peter Shen: And so I think there are multiple layers and it to to gain that expertise. But we're in that crowded one on one is a good starting point for that.
137
00:20:08.760 --> 00:20:19.069
Eva Amsen: And and do you think, that over the years the instruments have become more user, friendly like? Are are there more entry level instruments. Now for people to start using.
138
00:20:20.270 --> 00:20:25.510
Peter Shen: I definitely think that the field has progressed in the right direction in this regard.
139
00:20:25.810 --> 00:20:30.110
Eva Amsen: so does that make it easier for students?
140
00:20:30.140 --> 00:20:33.020
Peter Shen: It it does. And I think,
141
00:20:33.700 --> 00:20:41.720
Peter Shen: I would say, for most in my experience, most students probably don't have as much time
142
00:20:41.780 --> 00:20:45.910
Peter Shen: in front of the microscope or driving on the microscope as
143
00:20:46.170 --> 00:20:48.600
Peter Shen: as they deserve.
144
00:20:48.740 --> 00:21:04.150
Peter Shen: And you know, depending on the facility. For example, it's understandable if you know, if you don't want to trust complete newbies to to fiddle around with your multi 1 million dollar instruments. But
145
00:21:04.160 --> 00:21:15.989
Peter Shen: along those lines, though it's the level of involvement to. For example, align. A microscope has been greatly simplified even to the point of automated
146
00:21:16.040 --> 00:21:20.450
Peter Shen: compared to, you know, 10 plus years ago.
147
00:21:20.760 --> 00:21:21.850
Peter Shen: And so
148
00:21:22.490 --> 00:21:28.950
Peter Shen: I would say that a lot of the skills that I learned as a training are probably considered antiquated, you know in terms of
149
00:21:29.040 --> 00:21:33.880
Peter Shen: you know, aligning a side entry microscope
150
00:21:33.960 --> 00:21:37.710
Peter Shen: or even operating a side entry holder. I think
151
00:21:37.850 --> 00:21:52.029
Peter Shen: you know the fewer and fewer institutions are supporting those types of instruments. And you know, seeing the new microscopes that are coming out, where, for example, you have dedicated screening microscopes that are pretty automated.
152
00:21:52.100 --> 00:21:56.020
Peter Shen: And so I think the level of
153
00:21:57.040 --> 00:22:03.349
Peter Shen: maybe not necessarily the level of expertise. But the the focal point of the expertise have shifted
154
00:22:03.420 --> 00:22:05.229
Peter Shen: hopefully here. It's where.
155
00:22:05.640 --> 00:22:18.370
Peter Shen: you know. I don't know how many hours I've spent in, for example, developing film you know,
156
00:22:18.490 --> 00:22:24.910
Peter Shen: And so for my own training, I'm I'm sensitive to this when, as I'm bringing in new graduate students and post docs that
157
00:22:24.920 --> 00:22:32.159
Peter Shen: I'm thinking about, you know. Is it really worth your time, you know. Would it make you more marketable if you
158
00:22:32.320 --> 00:22:35.750
Peter Shen: if you had these skills and
159
00:22:35.950 --> 00:22:49.269
Peter Shen: maybe less so, and I would rather have them spend their time on on using state of the art instrumentation so that they can focus more on their own objects rather than the technical expertise
160
00:22:49.600 --> 00:22:51.800
Eva Amsen: that makes sense. Yeah, thanks.
161
00:22:52.180 --> 00:23:04.630
Eva Amsen: I want to change directions slightly and ask you, So we've talked a lot about. But we can cry, I am. But what do you like to do when you're not working? Do you have any hobbies or
162
00:23:04.740 --> 00:23:08.340
Peter Shen: hobbies? Some things that come to mind
163
00:23:08.850 --> 00:23:29.640
Peter Shen: I like playing basketball and so our department, we have a a weekly series of pick up basketball that's led by graduate students and post docs, and they've been generous enough to let that old faculty members like myself join them up with them. But
164
00:23:29.980 --> 00:23:31.969
Peter Shen: That that is one hobby.
165
00:23:32.240 --> 00:23:39.789
Peter Shen: I'm at a stage of my life where a lot of my time is focused on the 3 kids that that I have
166
00:23:39.970 --> 00:23:51.099
Peter Shen: ranging from elementary to to middle school. And you know, that comes with a lot of time spent on sports and music lessons.
167
00:23:51.250 --> 00:23:56.090
Peter Shen: but turning that into also a hobby where I'm
168
00:23:56.270 --> 00:23:59.959
Peter Shen: practicing sports with all we're playing music with them
169
00:24:00.210 --> 00:24:05.820
Peter Shen: And then just over the and I would say
170
00:24:05.860 --> 00:24:26.110
Peter Shen: another hobby that comes to mind something that we've picked up over the past few years is, really enjoying the great outdoors here in the top. Just have so much access to to beautiful wilderness, including 5 national parts. In fact, just this past weekend. Now, we spent the weekend down at a national park, and
171
00:24:26.110 --> 00:24:43.009
Eva Amsen: got to get away from the city for a little bit
172
00:24:43.010 --> 00:24:56.110
Peter Shen: travel to to go outdoors. You know I didn't go to my first national park until about 5 years ago. I spent most of my life here in Utah.
173
00:24:56.150 --> 00:25:17.219
Peter Shen: but I certainly didn't take advantage of of the beauty that we have here until most recently, and that was part spurred by. you know, kids getting older and just leading to find more bonding activities. And, boy, I just think about how much I've missed out on not taking advantage of that sooner.
174
00:25:17.560 --> 00:25:18.500
Eva Amsen: Yeah.
175
00:25:18.790 --> 00:25:27.529
Eva Amsen: And and and when you were indoors, do you? Do you have any like things like, do you like reading or films or music.
176
00:25:27.860 --> 00:25:32.210
Eva Amsen: any recommendations, perhaps, for our listeners.
177
00:25:32.260 --> 00:25:36.559
Peter Shen: When I'm indoors
178
00:25:37.490 --> 00:25:51.219
Peter Shen: we at home we play a lot of board games. it's fun where you know the the the kids are at the point where we can play more strategy based games. So we definitely
179
00:25:51.460 --> 00:25:56.260
Peter Shen: it depends on who you're with, I would say, if you're with
180
00:25:56.350 --> 00:26:03.110
Peter Shen: a bigger group, and you like chaos One game that we love is called Captain Sonar.
181
00:26:03.280 --> 00:26:32.299
Peter Shen: I don't know if you've heard of it, but it think of it as a battleship on steroids where you have 2 teams that is in charge of navigating a submarine, but trying to blow up the other submarine. And so the 2 teams are sitting on opposite sides of the table, and things are happening in real time. And so people are talking over one another, and you're trying to eavesdrop and keep track on what the other team is doing. And so that's that's a lot of fun.
182
00:26:32.310 --> 00:26:42.969
Peter Shen: now, we we like a lot of puzzle based games. you know, mixing, mixing, and matching certain tiles. So the game a zoom comes to mind.
183
00:26:43.290 --> 00:27:07.139
Peter Shen: Another party game that we go to again that we like is called code names. But anyway, there, there's so many. So I think if you open our closet at home, there's more than 100 games, and some of them are probably still shrinker at. So that's something that our family definitely enjoys indoors. So the other thing is that we're
184
00:27:07.340 --> 00:27:21.470
Peter Shen: We like music. And so I play the piano. My wife plays the cello and our kids play different instruments. We have someone learning the viola
185
00:27:21.700 --> 00:27:27.740
Peter Shen: something for the violin, and so like find songs where we can
186
00:27:27.880 --> 00:27:54.099
Eva Amsen: play with each other or a company. yeah, that's great. I I actually play violin myself. So I love hearing that. And your kid that's learning via life is going to have a lot of options, because all the orchestras are always short of vonless. That was a little bit of a tactical decision when you think about what instrument you wanted to pick up. And so yeah, he's enjoying it. Yeah, that's great.
187
00:27:54.390 --> 00:28:03.089
Eva Amsen: Another question that I love asking people is, if you were not a scientist, what would you be? What would you do? Have you ever thought of that?
188
00:28:03.890 --> 00:28:05.539
Peter Shen: Certainly thought about it.
189
00:28:06.050 --> 00:28:19.580
Peter Shen: I think, probably in a practical sense. I come from a family of lawyers. and it's actually something that's career track that I considered
190
00:28:19.720 --> 00:28:24.720
Peter Shen: after graduate school, something that I considered, you know, in the middle of my post. Stop!
191
00:28:24.860 --> 00:28:33.439
Peter Shen: I don't think I would have been very good at it but my in a practical option. But in terms of
192
00:28:33.800 --> 00:28:39.859
Peter Shen: things that would be more fun. I thought about
193
00:28:39.940 --> 00:28:44.450
Peter Shen: food trucks something about
194
00:28:44.510 --> 00:28:54.070
Peter Shen: operating a mobile kitchen that has always drawn to me and some of my favorite food as ours is from food trucks. And so
195
00:28:54.220 --> 00:29:05.609
Peter Shen: yeah, when I was a boy. I wanted to be a pizza delivery driver, so you can tell that I'm I'm I'm drawn to food.
196
00:29:05.860 --> 00:29:12.310
Peter Shen: well, I like. So after just saying that I would operate the truck.
197
00:29:12.700 --> 00:29:23.790
Peter Shen: I would say I'm very privileged to have very talented wife who cooks very well.
198
00:29:24.070 --> 00:29:29.330
Peter Shen: And she, you know, explores different cuisines. And so I've definitely benefited from that.
199
00:29:29.410 --> 00:29:48.799
Peter Shen: I really like to make sushi something we do on a pretty regular basis. and so but that that might be the extent of my culinary school. Well, that's pretty difficult. I can never get the rules to stay together. So the rice having a really good rice. Now.
200
00:29:49.520 --> 00:29:52.300
Eva Amsen: thanks for that tip. Gonna try it again now.
201
00:29:52.720 --> 00:30:10.359
Eva Amsen: And the last thing I wanted to ask you is we always ask for guests for a little piece of advice, and I think with your experience in cry way, I'm training Is there any piece of advice that you would give students who are interested in a career that involves.
202
00:30:14.760 --> 00:30:19.879
Peter Shen: I would say, the first thing that comes to mind with that question is something that I tell
203
00:30:19.970 --> 00:30:23.320
Peter Shen: everyone who's interested in joining my lab
204
00:30:23.500 --> 00:30:25.309
Peter Shen: is that
205
00:30:25.390 --> 00:30:31.100
Peter Shen: you know, as long as they're surrounded it in this environment is to ask questions.
206
00:30:31.240 --> 00:30:32.250
Peter Shen: Oh.
207
00:30:32.870 --> 00:30:36.549
Peter Shen: in my experience that's always been the fastest way to learn.
208
00:30:36.830 --> 00:30:48.609
Peter Shen: And I would say, it's even more important. So now Because my my sense is that you know we we have moved into a more
209
00:30:48.820 --> 00:31:03.329
Peter Shen: isolated mindset. naturally, because of the pandemic and the merging out of the we've gotten used to isolation and gotten used to trying to figure things out on our own. I think to an extent we have to do that we have to do our own due diligence.
210
00:31:03.460 --> 00:31:05.370
Peter Shen: but
211
00:31:05.740 --> 00:31:11.029
Peter Shen: for trainees out there who have the benefit of being surrounded by expertise.
212
00:31:11.040 --> 00:31:12.520
Peter Shen: Ask questions
213
00:31:12.530 --> 00:31:17.389
Peter Shen: I love it when people can just walk into my office and just wanna on the chat.
214
00:31:17.610 --> 00:31:25.149
Peter Shen: I love it when people drop me cold call emails, you know, after browsing crowded, and one on one and wanting to learn more.
215
00:31:25.270 --> 00:31:30.700
Peter Shen: And I always make it a point to to respond, to to call call emails
216
00:31:30.930 --> 00:31:37.820
Peter Shen: So that that's the first thing that comes to mind is to ask.
217
00:31:38.910 --> 00:31:59.970
Eva Amsen: That's great advice. And yeah, I think that's a that's also a good thing to close on after I asked you so many questions, and you've encouraged people to ask more questions. I think that brings us to the end of our episode today. So thank you very much, Peter, for being our guest today, and thanks everyone else for listening to or watching, cry out, talk.
