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EMN Webinar 20231025 - October 25, 2023 — Transcript

by Metabolomics Society · 10,575 words · 1,643 segments · language en · Watch on YouTube

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0:00on this
0:03computer and then I'll
0:07start the
0:13webinar see my
0:28screen
1:40good afternoon everyone or morning
1:43depending on your time zone we're just
1:46going to give it a minute or two for
1:48more people to log in and then we're
1:49going to start kickart our
1:58webinar
3:01hi Dominica can you see the screen
3:13fine yes yeah yeah yeah I can okay I
3:17think we can uh start
3:28now
3:56uh
3:57good good afternoon or good good morning
4:00everyone my name is Anar maana from
4:04South Africa I'll be co-hosting with uh
4:07Miss
4:09Dominica um baradi and our two speakers
4:13for this afternoon are Dr Sim shongo and
4:17Miss Pano marari both from the
4:20University of Johannesburg and they will
4:22be taking us through metabolomics at the
4:26Forefront of plant micro micro inter Cs
4:30and phyto chemistry um Miss um Dominica
4:36will introduce Miss panari later in the
4:39session and I will just start off by
4:42introducing uh
4:50drongo uh but first please check out our
4:54social media Pages we have a Facebook
4:58page uh under the metabolomic society
5:01and on X formerly known as Twitter we
5:04have the emn uh page that you can please
5:07follow us for any emn related activities
5:11and then we have the metabolomic society
5:15uh uh Twitter page or X page that you
5:18can also follow for all the other uh
5:21updates and then if you have any
5:23inquiries or would want to reach out to
5:25the metabolomic society you can reach us
5:29through
5:30uh the email and as I have indicated
5:32this are the speakers for our afternoon
5:35today and then I will just hand over to
5:40um Dr shortly after I read out his
5:51bio uh Dr mimo is an is an independent
5:55researcher at the University of
5:57Johannesburg in South Africa in 2015 he
6:00obtained his master's degree in
6:02Biochemistry and received the best
6:04master student award in the department
6:06of biochemistry in 2016 he he received
6:11the sa s23 bronze medal from the faculty
6:15of science for his contribution to the
6:17advancement of science through his
6:19master's project in 2018 M was appointed
6:23as an assistant lecturer in the
6:25department of biochemistry and in 2020
6:29he completed his PhD in Biochemistry
6:31upon the completion of his PhD MC was
6:34appointed as a lecturer in the same
6:37Department he he was also promoted to a
6:40senior role in that particular
6:42Department his re research activities
6:45are divided into two categories the
6:48first one plant microb or micro microb
6:51interactions and then the second one
6:53phytochemistry and discovery of drug
6:56likee products um drongo was was also
6:59part of the emn a few years ago so we
7:02are excited to have him back sharing
7:04some of his research over to you drongo
7:08you can start sharing your slides and
7:09then uh take over for the
7:28presentation
7:36uh greetings everyone uh in a second I
7:40will just deal with the technical issue
7:42that I'm experiencing then I will share
7:44my screen I'm not so sure if it's
7:46visible on your
7:49site yes can you my screen I just went
7:53away right now please okay try again uh
8:01can you see my screen now yes and my
8:05presentation yes you can just go
8:09perfect okay uh greetings everyone thank
8:12you very much for the introduction and I
8:13would like to thank the
8:15metabolic the metab the international
8:17metabolomic Society together with the m
8:20emn for allowing them the opportunity
8:22for me to present the research that I've
8:24been doing since the three years I
8:26started research at UJ so in short um my
8:30name isim and has been introduced I'm a
8:33senior lecturer in the department of
8:34biochemistry and this year I served as a
8:36deputy hod for teaching and learning in
8:39the same department and today I'm very
8:41pleased to be sharing with you my
8:43presentation which I decided to title PL
8:45growth promoting rise of bacteria the
8:47Messiah of plant growth protection and
8:49sustainable and sustainable agriculture
8:51sustainable farming uh I had to think a
8:55bit far or a lot about the topic and and
8:59I choose the term Messiah because these
9:01organisms seems to be able to do it all
9:05when it comes to plant protection plant
9:06growth promotion and also the potential
9:09that they possess in agriculture that
9:11you can use to them so
9:14um please excuse me I'm a bit nervous
9:17but I'll try by all means to remain calm
9:19throughout the presentation this is the
9:21overview of my presentation just need to
9:25get my point this is the overview of my
9:26presentation which I'll will start by
9:28just giving a information about the
9:30University of Johannesburg the
9:31metabolomics at u.j the problem that we
9:34face in terms of food security versus
9:36the the population changes in Global
9:39Food um challenges that we have in
9:41global food production I'll introduce
9:43plant microb interaction PL growth
9:46promoting rise of bacteria and then I'm
9:48going to use a series of studies that we
9:50did on weight priming by uh pgpr on
9:53stripe R to to explain why this organism
9:56sort of hold the potential in the
9:58applicate in agricultural
10:01applications so the University of
10:04Johannesburg is a public university that
10:06is situated in Johannesburg in South
10:08Africa it came to existence on the 1st
10:10of January in 2015 as a result of the
10:13match between the rent Africans
10:15University and the technicon uh the vest
10:17veran technicon together with the social
10:20Soto and the East Rand um campus in the
10:23Vista University this is a vibrant
10:26University it's Multicultural and
10:28dynamic it's sharing a space with the UN
10:30with Johannesburg which is the city
10:32which houses this University and it's a
10:34proudly it's a proudly South African
10:36University which is well prepared for
10:39its role in actualizing higher
10:41education's potential in the continent
10:43and also in the country the university
10:45houses a total of eight faculties that
10:47are spread throughout um four campuses
10:50and the department of biochemistry is
10:52situated in the Oakland parkings way
10:54campus which is the main campus of the
10:56university and when you take a look at
10:58the University you can see this is our
11:00campus that we are and the department of
11:02bims is found here on the on the cabs on
11:05the top floor so this is where you will
11:07find the department of
11:10biochemistry okay so back to metabolomic
11:12at ugj um in 2008 Prof duberry in
11:17collaboration with
11:18csir received an NEP grant for the syap
11:22G1 uhplc Ms this instrument has been
11:25with us for almost more than 14 years
11:27and has graduated a number of students
11:29of which some are not depicted here but
11:32these are some of the student that
11:33remained in research so the first the
11:36pioner of metabolomics at .j was Prof
11:37duberry since 2008 2008 and then he has
11:41trained a number of student but I would
11:43like to highlight two that are still
11:45involved in research one of them is Prof
11:47madala who has since moved to University
11:49of Venda hence I used the doted red
11:51lines there red lines just indicated the
11:53students that were trained by Pro in
11:56metabolomics Dr tokis is still with us
11:58here at. I put myself a bit lower there
12:01and I've got those green arrows because
12:03the two have P their knowledge to me as
12:05I was a student so I'm sort of behind
12:08them I came after them and I joined the
12:10metonic group and then I have blue lines
12:13there that are dotted lines which shows
12:15that I still have collaborations with
12:17the three pioneers of metabolomics at .j
12:21the gray lines the doted gray lines
12:23indicate collaborations that have been
12:25included Prof duber together with Dr to
12:28they Co supervised one of our Master
12:30student who's now doing PhD and this
12:32project is one of the of of the results
12:34that I'm going to use um to explain the
12:37use of pgpr in
12:39agriculture and then the solid gray
12:41lines just indicate the ongoing
12:44collaboration between the two as you can
12:46see Prof Madara still supervised two of
12:48my student in phytochemistry natural
12:51product research and also one of my
12:52students also Co supervised by
12:54Dr so my research um I'm a very
12:57ambitious person
13:00uh so my research spans a lot of areas
13:02in plant microb
13:05interaction where we try to elate the
13:08action mechanism that involve when
13:10microorganisms interact with one another
13:12either the micro being a pathogen or
13:14being a beneficial
13:16microorganism also this year with two of
13:18my student which is n together with we
13:22started to introduce something that is
13:24called micro microb interaction we are
13:26trying to eluate mechanisms of action
13:28between the microorganism be it to pgpr
13:31microorganism that interact with one
13:32another or be it a pgpr together with a
13:35pathogen just to see how these
13:36microorganism interact with one another
13:38then on the phytochemistry side I've got
13:40a lot of Master student but here this
13:43research is still at its very very early
13:45stages panel will share what we've been
13:47able to accomplish so far but um it's
13:50mostly the profiling of the plan
13:51medicinal plant that are found in South
13:53Africa trying to elucidate the action
13:55mechanisms using comput computational
13:58tool such as Network pharmacology and
14:00molecular docking however we still look
14:02for um collaborators and everything so
14:05that we can really take this further and
14:08maybe it could result to the discovery
14:09of other drugs that can be used to treat
14:11various
14:13diseases so back to the business um we
14:17know that um we have to produce and
14:20maintain human survival on Earth however
14:23the rate at which we are producing is
14:25alarming and this rate when is starting
14:27to be compared with the food demand
14:28every time we produce a new person is
14:30introduced that person put pressure on
14:33the food production and that H sort of
14:35threatens the food security that we have
14:38so Studies have shown that um in order
14:41for us to meet the food demand that is
14:43depicted in 2050 there should be a rapid
14:46increase in food production one of these
14:49especially the developed countries those
14:51countries don't need a lot of increase
14:53they just need like right around about
14:5412% but countries especially in Africa
14:57that are developing which are also some
14:58of the countries that are sort of living
15:01in poverty we will need approximately
15:04115% of increase in food production in
15:06order to meet that demand furthermore um
15:10the land the Earth as we continue to
15:13grow as we continue to grow the
15:15population and everything the aable land
15:17Remains the Same as you add more people
15:20the hector per person also shrink as you
15:22can see here that the number of people
15:23continue to increase but when you look
15:25at the hector per person is also going
15:27down this means that will have less land
15:30to produce food at the same time we will
15:31have um a high demand of food from the
15:35population that we have so there is a
15:37necessity for interventions in order to
15:39make sure that by the time the
15:41population reach 2.5 billion will be
15:43able to reach to to produce enough food
15:46for
15:47all so um the food industry which is mly
15:51the primary industri is the agricultural
15:53industry that deals with the farming the
15:54production of food the big crops or
15:57animal or anything they all depend on
15:59crops the reason for that is that plants
16:01are able to harness the energy from the
16:04light together with carbon dioxide to
16:05produce different um compounds that are
16:09suitable for their growth and
16:10development and also we benefit from
16:12that as humans so it's important that um
16:15we meet these challenges that plants
16:17face on Earth so in nature plants are
16:21faced with a different of stresses
16:22ranging from biotic and biotic stresses
16:24that impact their survival and their
16:27growth so this have a negative impact
16:30and when you look at the agure industry
16:31this reduces the output that the Agri
16:34industry can have so and um it is known
16:39that plant rely on their innate immun
16:41system but however this is not always uh
16:43successful so the plant can either
16:45disease get diseased from a pathogen or
16:47succumb to whatever stress that they are
16:49experiencing and that also reduces the
16:51output from agricultural
16:53industry number two is that we switched
16:56as humans which I believe we are the
16:58most problematic species on Earth we
17:01always find the simplest solution that
17:03we think are the best solution and
17:04fewest down the lines we then discover
17:06that these Solutions are not the best so
17:09to combat all of this we either did
17:11resistant breeding which allow us to use
17:14extensive use of
17:15agrochemicals also you've got plants
17:17that are resistance to different
17:19environmental conditions the use of
17:20agrochemicals has been on the rise and
17:22everything all of this from genetic
17:25modification and the use of
17:26agrochemicals has led to
17:29and environmental concerns as they are
17:31detriment to environment thus there is a
17:34need for potential sustainable solution
17:37one of these is the good or
17:39microorganisms that are found in the
17:40rizosphere or even within the plant that
17:43have been shown to have um a a better to
17:47be a better solution for agricultural
17:49explanation expansion however this or
17:52use of these organism is limited because
17:54there's no sound science that support
17:56their use and it's mostly based on
17:57people telling other each other that
17:59this one performs better this one
18:01doesn't perform better so there's a need
18:03for us to investigate the scientific
18:05mechanisms and also to support these
18:08studies and the use of this uh organism
18:10also to help the government to come up
18:12with legislations that could force
18:14Farmers to sort of switch to these
18:17organisms so in order for me to
18:20introduce plant growth promoting rise of
18:22bacteria I decided to select two review
18:24articles that we've written one was
18:26written by me in 2018 when I was doing
18:28my research and the other one was
18:30written by my student Dennis recently
18:33during his master study so if you want
18:35to know more about PL growth promoting
18:37rise of bacteria please feel free to go
18:39and read these articles but I'll try by
18:42all means to cover as much as I
18:45can okay so as we know in nature plant
18:49encounter different microorganisms these
18:50microorganisms can either be Pa
18:52nonpathogenic they can be pathogenic and
18:55they can be beneficiary microorganisms
18:57the inter differs depending on the
19:00organisms so we all know that plant have
19:02a preformed defense which is the first
19:05line of defense that prevents the entry
19:07of the microorganism into the plant and
19:10these preformed defense are there to
19:11defend the plant from this pathogen what
19:13happens is that the pathogen when you
19:15look at the nonpathogenic microorganisms
19:17they can either be stopped by the pre
19:19preformed defense uh system or they can
19:22buypass it which means that now they are
19:24within the plant but these are not
19:25problematic when the plant recognizes
19:27this it will activate different um forms
19:30of Defense responses however this can
19:33lead to the plant being Talent or being
19:35induced for for protection against other
19:38microorganisms these ones do not have
19:40any effect on the plant so the plant
19:42will eventually come back to homoy to
19:44realize that there are no other um
19:47damages that are occurring in the plant
19:48due to the presence of these organisms
19:51the other ones are pathogenic
19:53microorganisms there are two events that
19:55could happen when the pathogen infect
19:57the plant can bypass the first line
20:00defense induce a defense response
20:02however that defense response can be
20:04insufficient which means that it can
20:05cause an infection which then could lead
20:08to disease which means that the plant
20:10now is is is in a disease State and it
20:12will then succumb to the infection from
20:14the pathogen on the other hand if the
20:16plant is stronger enough it can then
20:19survive the infection and that would
20:21leave the plant with a memory or a
20:24memory to sort of also defend it better
20:27to defend better against the same
20:28pathogen or other pathogen in the near
20:30future so the plant after that is then
20:32set to be toorent or resistant the third
20:35form of microorganisms that happens that
20:37there is a The Beneficial
20:40microorganisms these microorganisms can
20:42either be found on the surface where
20:44they perform their beneficial effect to
20:46the plant or they can also be found
20:48within the plant the interesting about
20:50these organisms is that they do not
20:51cause any harm to the plant but they
20:53support the plant there are various
20:56chemical events or biochemical events
20:58that takes place that allows a
21:00successful interaction between the plant
21:02and the pgpr and this is driven by
21:05mostly of the metabol and once this
21:07interaction is is is in place the
21:09metabol becomes very complex because it
21:11then becomes difficult to see which
21:13metabolites come from which organism and
21:16we are stucked here as scientists
21:19because we cannot really tell uh whether
21:22the pgbr the once this organism interact
21:25which metabolites come from which
21:26organism and everything and that's where
21:28we are stuck but there are tools that
21:30have been developed that are able to
21:32help us with
21:34that so as I said that these organisms
21:37facilate plant growth as you can see
21:39that they are mostly found in the risos
21:41spere those are the ones that I deal
21:43with the plants secrete root exodos the
21:45root oidos recruit different pgpr which
21:48perform various functions one of them
21:50being nitrogen fixation solubilization
21:53of nutrients and decomposition of
21:56biological material to make sure that
21:58the nutrients from the soil are also
21:59available and then this results in
22:01increased photosynthesis which means
22:03that the plant grows better it can
22:04photosynthesize it has more energy can
22:06acquire more energy from the Sun and
22:08then it can grow and also the plant has
22:11an increased biomass which means that
22:12the plant that have been treated by pgpr
22:14have been shown to be bigger compared to
22:16plants that are not treated with pgpr
22:18furthermore the yield output is also
22:20increased Studies have shown that you
22:22get around about 40 20 to 40% increase
22:24in YK which is good for agricultural
22:26industry another benefit is the
22:29induction of resistance against
22:31environmental stresses so these
22:32organisms as said that they are Messiah
22:35they seems to have a vast number of
22:37organisms of of benefits to the um to
22:41the
22:44plant so how this organism interact or
22:47what events that takes place when this
22:49organism interact there are events that
22:52takes place in the risos spere the first
22:54thing is that reduce oxidos will recruit
22:57a specific strains and these strains
22:59will be recruited by the root Exodus
23:01from there this organism can also
23:03recruit other microorganisms through
23:05chemical secretion so they secrete other
23:07chemicals that can recruit other
23:09microbes and that then builds the
23:11population of microorganisms that is
23:13found in the rizosphere
23:15moreover this organism can have
23:17inhibitory effect on pathogenic
23:20pathogenic bacteria through the release
23:22of also signaling molecu antibiotics
23:24Soros and so forth and then they can you
23:27have also the soil bone pathogens which
23:30could be uh effective um affecting the
23:32plant and so on so this organism can
23:34help to prevent infection from soil born
23:36pathogen so all this interaction that
23:39takes place in the rizosphere result to
23:41metabolic pupation or
23:44biochemical pertubations event or
23:47biochemical events that happens in the
23:49crop plant for priming purposes there
23:51are three steps that you discover one is
23:54the signaling once the organism is
23:56perceived or the signal from the
23:57organism is perceived they are signaling
23:59events that is driven by phyto hormones
24:01and other signaling molecules these
24:03initiate defense responses and
24:05everything and then these distance
24:07responses will result in the modulation
24:09of the primary and secondary metabolites
24:12and then this renders the plant a faster
24:14and stronger immune response to broader
24:16spectrum of resistance it could be your
24:19pathogen it could be abiotic stresses or
24:21biotic stresses and then the plant is
24:24said to be primed from that also it
24:27could drive inter Direction what we call
24:28allopathy to other organisms so when a
24:30plant is treated by one it can also
24:32notify the neighboring plant of what is
24:36happening as I said that there are
24:39cellular events that are taking place
24:41between the two interacting organism
24:43that result in the mutual relationship
24:46between the two some of these mechanisms
24:48are not really
24:49elucidated or they are not really known
24:52thus we in one of the review we then
24:55postulated this diagram so what happens
24:59that the plant itself will secrete what
25:01we call Root oxidos through transporter
25:03proteins to the risos sphere this can be
25:06picked up by the microorganism through
25:09there are receptor proteins that could
25:11facilate different signals or they can
25:13diffuse through the membrane and they
25:15can drive the cell metabolism of the
25:17pgpr there are events that are really
25:20really not known at the moment but these
25:22events lead to expression of genes that
25:26are related to the production of phyto
25:28hormones certain volatiles and cidos
25:30antibiotics and other molecules that are
25:32beneficial to the plant and these will
25:34then be secreted outside through prot um
25:38transporter proteins and they secr to
25:40the rizosphere the plant can pick up
25:42these signals that are processed today
25:45and it leads to different um cellular
25:48events all the way there and then it can
25:50lead to induced resistance so this is
25:53just a simplified diagram that we came
25:54with but there could be other events
25:56that are taking place so that's why
25:59science is still needed in order to
26:00elate the action mechanisms of these
26:04organisms so enough about pgpr let's
26:07come back to the series research that
26:10I'm going to study in this study what we
26:12did we wanted to see the priming effect
26:14or the ability of this microorganism to
26:17induce resistance against a strip rised
26:20fungal disease on wheat so why wheat
26:23wheat is the second most produced crop
26:25worldwide and it's processed to
26:27different products that we eat on our
26:29daily basis and also it's a stable it's
26:31a stable food for most of the
26:34countries um in recent years it had been
26:36seen that the production of wind of
26:38wheat is declining especially in South
26:40Africa and this is due to climate change
26:44reduced in aable land and diseases such
26:46as strip rice so this is just the over
26:49view of the global production of wheat
26:51in South Africa uh as you can see that
26:55the area harvested is indicated in red
26:59and you can see that as years goes by
27:00the area becomes smaller and you can see
27:03that even though the yield is increasing
27:05and increasing stripe R is sort of
27:07becoming more and more of a problem in
27:09South Africa and thus we decided to do
27:12to do this
27:13research so strip R is caused by the
27:18pis Tre which is referred to as strip R
27:22it's a FAL disease it Thrive mostly in
27:24cool and most environment and in suable
27:26cultiv cause 10 to 100% food um losses
27:31yield losses in crop plant and it was
27:34reported in South Africa in 1996 and in
27:37the subsaharan region Zimbabwe is the
27:39last country to be added into the list
27:42of countries with the this disease so
27:45far resistant breeding of cultiv and
27:48also plant breeding are the main
27:50mechanisms that are used these either
27:52have resistance Gene that are resistance
27:54to herbicide that are applied or
27:56agrochemicals that are applied to comact
27:57the disease or they've got resistance
27:59genes that are resistant to the pathogen
28:02itself the pathogen affects the leaves
28:05and reduces the ability of the leaves to
28:07photosynthesize as you can see here
28:09you've got Dead Leaves where it has
28:11killed uh some of the leaves and also
28:14you've got these spores orange spores
28:16that cover the leaves totally which
28:17means that now the plant will have
28:19reduced photosynthesis and when that
28:20happens it means that the BL cannot grow
28:23well and that then lead to um
28:28reducing
28:29yield so this disease is said to be an
28:32Airborne which is becoming most of a
28:34problem because sometimes in South
28:36Africa we've got wheat that are grown in
28:38Winter and some that are grown in spring
28:40in different season and we know some
28:42season are windy some are not so it can
28:44spread to other crop plant to it and
28:48when the environments are unfavorable it
28:49can also survive on voluntary H plants
28:52until the environment are very favorable
28:54and then you can start infecting with um
28:58uh plants
28:59gave um so fungicides and everything
29:02have becoming the the the main
29:05mechanisms of um controlling this
29:08pathogen and also the breeding of
29:09resistant cultiv as I said the use of
29:12agrochemicals is in problem to the
29:15environment and there's a need of
29:17sustainable agriculture and the pgpr
29:19comes into
29:20play so this was a series of a study
29:24that we did um the aim was first to use
29:27metab omics to see if we can be able to
29:29distinguish between susceptible cultiv
29:31and resistant cultiv the other one was
29:33to investigate the metabolic pation
29:36occurring on the risos spere of plants
29:39treated with pgbr and also on the plant
29:42metabol treated with pgb the other one
29:44was just to compare two suable cultiv
29:47after the from the cultiv that we used
29:49with to see if we infect this cultiv
29:52with the pathogen water the metabolic um
29:55um sorry excuse me what are the multi
29:58events that are associated with
30:00resistant cultiv and suable
30:04cultiv and the last one was to study the
30:06priming effect against the stripe rust
30:11so on onset as I said we started with
30:13the metabolic comparison here we had
30:15four cultiv that we obtained from Arc in
30:19Bethlehem this ctiv cultiv has a varing
30:22resistance and sus ability to aluminium
30:24toxicity and also stripe rust so as you
30:27can see the first cultiv which was Al
30:30was suceptible to aluminium toxicity
30:33together with
30:34the uh um stripe rust there were two
30:38resistant cultiv toward stripe rust
30:40which was the kuna and the senu so Aon
30:43metab analysis we acquir the data and
30:45then we did some PC analysis to just to
30:47see the data structure in terms of ptin
30:49similarities differences between the
30:50cultiv on a two-dimensional PCA we could
30:53not really classify resistance from
30:56susceptible but um when we then did a
31:00three dimensional PCA we were able to
31:02tell the cultiv that are suble to and
31:06strip rust and
31:08toxx aluminium toxicity which was
31:12um it was
31:15Matas andand and
31:18then even was suceptible to toxicity to
31:22aluminium toxicity it was resistance to
31:25stripe rust and this you can see them
31:27here and the difference observed between
31:29the two could be due to
31:31their difference in in resistance or
31:34stability
31:36toxicity upon the metabolic annotation
31:38we able to annotate quite a number of
31:40metabolites and these metabolites belong
31:42to the classes that you could see here
31:44floid was the major class that we could
31:46identify which belongs to FX followed by
31:49hydroxamic acid and there were other
31:51metabolites that we able to
31:54identify then we then be did um
31:57a visual a closer look in the type of
32:00metabolizes that we could identify the
32:02first were the flavonoids the flavonoids
32:04were found to be more abundant in Kuna
32:07which is resistance in both aluminium
32:09toxicity and also uh stri R resistance
32:13um strip rice resistant as you can see
32:15here this is the kuna one you can see
32:17that the Flav were a bit higher on that
32:19together with the green one which is
32:21simple um not the green
32:24one uh yes this is supposed to be green
32:27which is the c one they were higher
32:30however when we look at the um fatty
32:34acid the opposite was true the suable
32:37cultiv which is harp matlas andand were
32:42higher in lipid like molecules and then
32:46lastly the feric acid the cafeic
32:48hydroxamic acid were also found more
32:50abundant in the suable cultiv so what we
32:55couldn't pick here was that there were
32:57no distinctive metabolites that we could
32:59associate between suable or resistance
33:02the metabolites were sort of differenti
33:04distributed in terms of quantity among
33:06all the cultiv and um it's only based on
33:12the accumulation especially the
33:13flavonoids which were mostly associated
33:15with the resistant cultiv towards thri
33:17breast so these metabolites such as your
33:20phenolic and everything they spend many
33:22physiological and adaptative processes
33:23in Plants such as morphological
33:25adaptation
33:27and mation reproduction development and
33:31defense against arotic stresses when it
33:33comes to defense they can protect plants
33:35against oxidative stress by scavaging
33:37free radicals that are results of
33:39reactive oxygen species they are said to
33:41be antimicrobial which means that they
33:43can inhibit pathogen growth they can
33:46also be incorporated into the C wall so
33:48that they strengthen the cell wall to
33:50prevent um more infection to the plant
33:54and lastly they can Cate metals and
33:57which is one of the mechanisms that you
34:00can use in order for crops that are
34:02mostly resistant to aluminium so they
34:05are able to Cate these um Metals in
34:07order to reduce their effect also metals
34:11can lead to reactive oxygen um re
34:13reactive damage which alsoo these crops
34:16um these metabolites can also protect
34:18against the other class that was mostly
34:20found in suceptible cultiv was the
34:22unsaturated fatty acid this they
34:25maintain the cell because they form as
34:27the constituent of the cell membrane so
34:30they help to to maintain the cells they
34:32also serve as precursors for the B
34:34synthesis of phyto hormon such as
34:35jasmonic acid jasmonic acid is a phyto
34:37hormone that is known for plant
34:40protection against atic and biotic
34:42stresses and also they can be signaling
34:45signaling molecules and Regulatory
34:47molecules they bind and regulate
34:48receptor proteins that control major
34:51networks such as your cellular
34:53metabolism and truction that could also
34:56be related to defense response
34:58interaction so overall this study that
35:00we have overall the outcome of the study
35:03revealed that significant metabolite
35:05variation in organisms could be both
35:07qualitative and quantitative as many
35:09metabolites were common among the five
35:11cultiv compared metabolic differences in
35:13the wheight cultiv resulted in apperent
35:15cultiv Associated differences based on
35:17genetic differences between the cultiv
35:20and genetical related can vary in
35:22metabolic
35:24contribution composition and
35:26distribution attributed to the phenotype
35:28and the functions of agrom
35:30properties in addition some distinct
35:33metabolic markers were identified from
35:35the selected whe cultiv for example
35:37quinic acid violin were identified as
35:39metabolic markers for the suceptible S
35:42um cultiva along with the unsaturated
35:46fatty acid and at some point um the kuna
35:51which was the resistant cultiv showed a
35:53higher accumulation of
35:55flavonoids so these were just the
35:57summaries that we had on the study and
35:59then we moved on to the other study
36:02which was now to look at the
36:05metabolic differences that are happening
36:07in the risos spere due to pgpr treatment
36:09and also to the plant which were treated
36:11by two um pgpr so I'll try to move F I
36:16think I'm falling behind
36:18time um the study was divided into two
36:21the risos spere metabol together with
36:23the plant metabol and then this was then
36:25analyzed through MPC and multivariate
36:28data analysis and together with
36:30molecular networking so from PCA point
36:33of view we were able to see that this
36:35the first one is um the harib which was
36:38the suble cultiva that was chosen and
36:42the second one is the Kun which was the
36:43resistant cultiv that was chosen these
36:46were then treated by two pgpr which is
36:48basila subas and P basil Al and as you
36:51can see in a the untreated were clusters
36:55away from the treatment ones and then we
36:57also have some time dependent clustering
37:00that was observed when we look at week
37:02one week two on the different
37:04cultivat and then we did some molecular
37:07networking from the molecular networking
37:08these are the classes of compounds that
37:10we could
37:11identify uh ranging from organic acid
37:14your benzo your lipids and everything
37:16benzo was the most significant class of
37:19metabolites that was found it is a
37:21metabolite that is sort of a taxonomic
37:23metabolite that is mostly found in Grass
37:24families and plays a different role this
37:27was discovered in the rizosphere the fin
37:29propan Pathways um they also found in
37:33the rizosphere and they perform
37:34different functions from antimicrobial
37:36to recruitment of other pgpr and
37:38everything and the lipid like molecules
37:41could play at different roles such as um
37:45protection of microorganism in the soil
37:47recruitment of them and also they serve
37:50as rubric that allows roots to penetrate
37:53the so without damage and so forth B are
37:57interesting because they also reported
37:59to recruit microorganism at the same
38:01time they also reported to inhibit soil
38:04bone
38:06microorganisms the organic acid can be
38:08suggested to be just organic molecules
38:11that are used by the interacting
38:13organisms or by the pgpr or by the plant
38:16secreted by them they are just there to
38:18serve as nutrient sources for the
38:20interacting organ especially the
38:22PBR so these were some of the studies
38:25that we have and then then we can move
38:27on to the plant now we then look at what
38:30effect do this PBR have on the plant and
38:33it did some data acquisition similar
38:36approach were then seen where your
38:39untreated was found to Cluster
38:41differently from this is the suable
38:42cultiv this the resistant cultiv you can
38:45see that um your untreated which is blue
38:48clusters away from the basila subas
38:51which is in red and the basas P the pine
38:54basas which is in green and then we then
38:56did some time Trend to look at what is
38:58happening here you can see in green is
39:01the harib treated with basilla saas here
39:05is har treated with the pine basas also
39:08here you can see the untreated there in
39:11and red and also the other different in
39:13terms of time and everything so there
39:15was a time Trend that was observed which
39:17could be postulated to the differences
39:19in the metab that observed thereafter so
39:23we did some also molecular networking
39:26these are classes of molecules that we
39:27found your lipid lipid like molecules
39:30which could be incorporated into the
39:31cell wall they also have antimicrobial
39:33activity um your organic acid
39:36derivatives and together with the final
39:38propanoid pathway when we then did the
39:40comparison between these you can see
39:42that you've got the resistant cultiva in
39:45red and also in green treated by the two
39:48bacteria and then this is the
39:49untreated um the resistant C suable
39:52cultiv which is har showed at higher
39:55accumulation after the treatment of
39:57these metabol that are observed here
39:59which belongs to flavonoids some
40:02thyrosin there which is very very
40:03important for Neal pathway so these are
40:06some of the metabolic changes that were
40:09induced by the basilla subas on the
40:13other hand the the pine billas which is
40:15this one here when treated by that
40:18causes the the accumulation of uh mostly
40:24um camic acid derivative benzoic acid
40:27derivatives and some of um flavonoid um
40:31related molecules so what we observed
40:34here was that um treatment of the suable
40:38ctiv lead to the production of phal
40:41propanoid pathway which is very good
40:44that you will see when we look at the
40:47defense responses of this um ctiv to the
40:50pathogen alone without priming and then
40:53we did some pathway mapping and
40:55everything that five pathways six
40:57Pathways that we found most of them were
41:00the citric acid pathway which just shows
41:02you that the energy production of these
41:05is then affected by the treatment of
41:07these organisms as you can see different
41:09metabolites were affected there the
41:11second best pathway was the carboxilic
41:13and dilic acid followed by the alanin
41:16and also the phal alanin tyrosin and
41:19tropen synthesis pathway which is
41:21presented here this pathway is very very
41:24important because it drives to the
41:25production
41:38of which
41:41are molecules that are known for the
41:44mechanisms when it comes to plant divers
41:46and the complex metabol of the risos and
41:48the P treatment indu metabolic changes
41:50in both the rizosphere and the above
41:52chemical space of the plant these belong
41:54to the phal propan pathway and and so
41:56forth and therefore we postulated that
41:59this study could serve as a basis for
42:02further studies to elucidate the action
42:05mechanisms H in the interaction below
42:07the risos
42:09spere the third study that was used was
42:11the metabolic profiling of suitable and
42:14resistant weight cultiv responding to
42:16the pathogen alone and same time we did
42:18some PC analysis you can see differences
42:21between treated and untreated of the two
42:23cultiv Kun up and what and then you can
42:25then a Time dependent what we observed
42:28here was that the
42:29untreated um um the untreated which were
42:34KN plants that were not infected they
42:37had sort of their own time Trend which
42:39could be due to growth of the plant in
42:41different weeks as you can see we
42:42sampled from week one all the way to
42:44week four and then we also observed that
42:47when you look at week one you can see
42:48there's a clear difference between the
42:50treated and untreated which also done
42:52now comes into play to explain that the
42:54treatment with the pathogen induced some
42:57metabolic differences when compared to
42:59the non-treated plant and then we wanted
43:01to investigate these metabolic
43:03differences we then did some annotation
43:05of metabolites and everything the
43:07resistant cultiv here showed a quick and
43:10faster accumulation of
43:14um metabolites that are involved in
43:16defense such as your flavonoids um
43:18signaling molecules and everything
43:20whereas these metabolites started
43:21accumulating later in the susceptible
43:25cultiv
43:26cultiva and then this then goes to say
43:28that the presence of flavonoid that was
43:30observed in the resistant cultiva play a
43:33role in the defense response of this one
43:34whereas this metabolite started to
43:37accumulate a bit later in the suceptible
43:41cultiva then the last study that we did
43:44was to evaluate the priming effect of
43:46this um pgpr to pgpr strains against the
43:50pathogen we did some PCA we could see
43:53some differences between the treatment
43:55and everything even though they were not
43:56apparent but you can see that the naive
43:58and control compared to the pgpr treated
44:01and everything there were some sample
44:03grouping and everything as you can see
44:04here you've got the control there which
44:06was week one and then you've got week
44:09one week two week three and then this
44:11cluster differently from the pgbr
44:13treatment uh treated um
44:16organisms uh plant it's important that
44:19here we only used aable cultiva after we
44:22observed that um when we primed this one
44:25it lead to the accumulation of
44:26flavonoids that were not observed to be
44:29higher in it when compared when we did
44:31the cultiva comparison also that we saw
44:34that the accumulation of this floid is
44:36sort of delayed when you infect this
44:38pathogen this uh cultiv with the
44:41pathogen so we then went on with the
44:42suable cultiv alone here to investigate
44:46what could is the uh pgpr able to Prime
44:51this
44:53um cultiva against the pathogen
44:57so through M results that I didn't show
44:59on the other plant but what we saw here
45:02that this is um the primed H plant this
45:08is the nonprimed plant you can see the
45:09spores the fer Spore on on this and you
45:12can see that the leaf is becoming yellow
45:15which indicates that the leaf is about
45:16to die whereas here the symptoms that
45:20the physiological parameters that we
45:23observed here were similar to that of
45:24resistant cultiv which is localized
45:27death and there were no fungal sports
45:29that were observed here which indicate
45:31that the pgpr which was Pine basas the
45:34t22 induced um resistant mechanisms
45:37against this pathogen when you compare
45:39the two also what we observed was the
45:42accumulation of hydroxycinnamic acid and
45:45um some flavonoids that were that high
45:49in the sustainable cultiv which was good
45:51because these floid seems to be the ones
45:54that play a role in resist of this
45:56cultiv against um the stripe
46:00rust and then various metabolites were
46:03found and these were found to be
46:04differentially distributed and they span
46:06the metabolites that I've talked about
46:08so in summary this study showed that in
46:11the nonre plant the organic acid were
46:14higher amino acid went down and the
46:17secondary metabolites which are e sweet
46:19specific metabolites was sort of
46:24higher um was sort of higher and this is
46:27the summary that we had which says that
46:29the TCA intermediate involv as
46:31precursors for cesis so you can just
46:34read this through I think I'm over
46:36time with that uh there are some ongoing
46:39research which uh various PhD and Ms
46:42student are involved in spinning from
46:44plant microb interaction and all the way
46:47to
46:49um natural products and phytochemistry I
46:52would like toally acknowledge my
46:53collaborators and plant micro
46:55interaction together with um
46:57phytochemistry and natural product
47:00lastly I would like to thank my student
47:01whom I don't believe this research would
47:03been a success if it wasn't involved
47:05them and here just want to show that
47:08they say that if you are a father two
47:09daughters you become soft as you can see
47:12all the men were not participating in
47:13this uh challenge but as a father I was
47:16involved there with all the ladies in my
47:17group so I also like to thank them
47:20lastly but not least I would like to
47:22acknowledge all these companies for
47:24their different contribution to my study
47:26and thank you very much I would like to
47:28hand over
47:29too who will show some information her
47:32research on natural product and
47:36phytochemistry thank you much drongo for
47:39your wonderful
47:40presentation I'll hand over to H
47:44Dominica to introduce Miss panari and I
47:47would like to encourage everyone to just
47:49type uh the questions in the chat box
47:52then drongo and uh our next speaker will
47:56address the questions towards the end of
47:59both presentations over to you
48:04Dominica yes uh thank you very much for
48:07the uh very brilliant presentation Dr
48:10wongo I would like now to uh introduce
48:13Miss uh Mafi uh she's an MSC student
48:17from the University of um uh janesboro
48:20uh under the department of
48:23biochemistry um where uh research
48:26involves the use of lcms based
48:30metabolomics in combination with
48:32molecular networking to decod the
48:35chemistries of asparagus species and
48:38further investigate their active
48:41compounds and mechanisms of action in
48:44alleviating uh malaria infection so uh
48:47please join me in welcoming uh Miss uh
48:50Mafi and um feel free to uh start
48:53whenever you're ready thank you very
48:55much
49:19um thank you good afternoon
49:22everyone um can you all hear me
49:27yes we can yeah we can hear it yeah yeah
49:29okay good afternoon everyone as
49:31introduced my name is paranor par and
49:35today I'll be presenting to you some
49:36work of my research project titled
49:38combining lcmsms molecular networking
49:41metaboli profiling with networking
49:43pharmacology to predict the antimalarial
49:45properties and molecular mechanisms of
49:47three asparagus PES in elevating malaria
49:50symptoms which is under the supervision
49:52of Dr and the co- supervision of
49:54pro Madara Dr Cen as well as um Pro
49:59Similan so this is the outline of my
50:02presentation so malaria is a major
50:04Global health problem causing
50:06significant mortality and Mobility
50:07annually it is a life-threatening
50:10infectious disease caused by the proten
50:13parasite of the genus plasmodium which
50:15is transmitted by the bite of the
50:18infected female Anil mosquito there are
50:21five uh plasmodium spaces that have been
50:23confirmed to uh
50:29okay there are five plasmodium spes that
50:32have been confirmed to cause malaria in
50:35humans and of this plasmodium palarum is
50:37the most virulent and the most prevalent
50:39of the plasmodium spaces treatment
50:42options for this disease are scarce and
50:45severely challenged by the emergency of
50:47resistant parasite which posed a major
50:49obstacle in malaria control however
50:52modern biologists are now uh uh mon
50:56biologist are now developing selective
50:59novel inhibitors for virus disease that
51:02thereby targeting uh the exploration of
51:05natural
51:06products asparagus is a medicinal plant
51:10from the genus asparagas with
51:12approximately 300 species that are
51:14naturally distrib worldwide and in this
51:17study we use three asparagus faes which
51:20are asparagus dtif floras asparagus
51:22Paras and plasmosis these plants are
51:25widely used as a neutral so people use
51:28this plants as a source of both Nutri
51:31nutritional and medicinal purposes the
51:33species within this plants has been used
51:36to treat virus alignments such as
51:38malaria pulmonary tuberculosis kidney
51:40infection I ey problems and infertility
51:43problems and this is because they
51:45possess pharmacological properties such
51:47as being antimalarial antimicrobial
51:49antibacterial and anti inflammatory
51:53however the metabolic choreography of
51:55this spaces is not well understood hence
51:58the compounds that contribute to their
52:00activities remains unknown so
52:03metabolomics which is the scientific
52:05study of small molecules in a biological
52:07system will be used in this study to
52:11explore the chemical composition of the
52:13these three aspara spes and metabolis
52:17comprises of four critical steps which
52:19are Illustrated here in figure four and
52:22I will explain them in more details on
52:25the methodology part furthermore
52:27metabolomics provides candidate links
52:29that can be used as a potential drug
52:33candidates for drug discovery which can
52:35be through compal tools such as
52:38molecular Ding and network
52:40pharmacology n pharmacology is the new
52:44scientific method that is being applied
52:46for the systematic multi pharmaceutical
52:48study of natural products with desire
52:51therapeutic indices this uh scientific
52:54method can help in understanding the
52:56mechanisms of multi acting Inhibitors at
52:59many scales from the molecular to the
53:02organism level by analyzing important
53:04features of the biological networks so
53:07figure five here is the network phology
53:10workflow which I will also um explain in
53:13more details on the methodology part of
53:16network phology
53:18analysis so the aim of this study was to
53:20employ lcms based metabolomics in
53:23combination with molecular networking
53:25decode the chemistry of three aspara
53:27species and investigate the antimalarial
53:30properties and therapeutic mechanism in
53:31treating malaria infection which was
53:35achieved by the following objectives the
53:37first one was to profile and compare the
53:39metabol of three aspar spaces using
53:41different solvent extraction to maximize
53:44The annotation of un using the inico
53:46tools house in GPS ecosystem and lastly
53:49to investigate the potential active
53:51ingredients and the mechanism of action
53:53of aspara species against malaria using
53:56system pharmacology and molecular doing
53:59so for the results and discussion for
54:02the first and the second objective which
54:04is comparative metabolized profiling of
54:06different solvent extracts of aspara
54:08species through lcms based metabolomics
54:10and M networking this is the methodology
54:14that U was used to obtain to to achieve
54:18those objectives so basically the leaves
54:21of the three asparagus spes were blended
54:24into fine powders and extracted using
54:28three different solvents with different
54:30polarities this is because in
54:31metabolomics extraction is cons
54:34considered as the most critical step
54:35that has an impact on the recovery and
54:39isolation of bioactive compounds in a
54:42plant sample and for efficiency of
54:45extraction several factors such as
54:47temperature pH time and the type of
54:49solvent use extractions are considered
54:52vital so in this study we consider the
54:55the type of solvent used for extraction
54:56as the most critical Factor affecting
54:59the efficiency of um extraction since it
55:02has an impact on the type of metabolize
55:05to be obtained so after extractions the
55:07samples were subjected to an ultra high
55:10performance liquid chromatography
55:11quadruple time of light mass
55:13spectrometry for analysis the data
55:15obtained was then uh the data obtain was
55:18then used for statistical analysis
55:20wherein PCA were generated on metab
55:24analyst Mo gnps molecular networking was
55:27then used to further visualize the data
55:29and vitabite annotation and for
55:32biological interpretation Pathways and
55:35heat Maps were also generated on metab
55:39analyst so figure six here is a
55:42representative Alam chatram of
55:45methanolic chlorop and ethy acetate
55:48extracts of asparagas den florus here
55:51was to show you the distribution
55:53patterns of metabolites among the three
55:55solvents or to show show you how each
55:58solvent was extracting and as you can
56:01see ethal acetate appeared as the poor
56:03solvent for extraction while methanol
56:06and chloroform extracted more
56:07metabolized and in a wide
56:10range so to determine the metabolic
56:13differences among the three spes and
56:16when extracted with different solvents
56:19uh pcas were generated on metab analyst
56:22so figure a to c it's P solvent
56:25comparison and D to a solvent P
56:28comparison so now looking at figure a to
56:31see which ises P solvent comparison uh
56:34samples of the three spes can be seen
56:37displacing in different region of the
56:39scope plot which indicate that the three
56:41species are significant different and
56:44also when comparing the solvents now a
56:47clear separation of Sol of samples can
56:50also be observed however when you look
56:53closely at figure
56:55the samples of methanol as well as
56:58chlorop can be seen clustering at the
57:00same point which suggest that this two
57:03solvent extracted similar metabolic
57:06Futures as compared to ethal
57:09aetate so to explore the chemistry of
57:13the three species when extracted with
57:15the three solvents molecular networking
57:19where molecular networks were generated
57:21so figure eight is an enhanced classical
57:25networking of asparagus spaces when
57:28extracted with e eal acetate when
57:32extracted with methanol and when
57:34extracted with chlorop so observing
57:37these results in a topological point of
57:39view it can be seen that the type of sol
57:43solvent use for extraction has an impact
57:46on the number of noes to be obtained and
57:49the networks and
57:51also uh the type of solvent used for
57:54extra ction also has an impact on the
57:57metabol chemical classification and as
58:00you can see eal acetate limited some
58:03chemical classification however it was
58:05the one which was able to extract more
58:08glycero phospholipids but on the other
58:12hand methanol was able to extract some
58:14of the metabolites which were which
58:17ethal acetate was unable to retrieve
58:20however chloroform was able to extract
58:23more metabolized compared to the other
58:26solvent and this results suggest that
58:28the type of solvent use for extraction
58:31has an impact on the type of metabolize
58:34that you would
58:35obtain so to further evaluate uh the
58:39effects of this three solvents on the
58:42network top topology as well as the
58:45chemical
58:47classification um the the major class of
58:52compounds we zoomed in so fig n here is
58:55a zoomed in cluster of
58:57glycerophospholipids
58:59wherein eal acetate was able to extract
59:03more
59:04glycerophospholipid and as you can see
59:06there are some of the metabolites which
59:08were specific to the solvents and some
59:11of the metabolites which were shed in
59:13within the species and some of the
59:16metabolites which were unique within the
59:19species similar approach was ABS
59:22observed with the camic aces however Tor
59:25was the one which was able to identify
59:28to extract more um camic
59:31acids even with the Flav noids however
59:34here there was a slight variation in
59:37terms of the number of of the number of
59:39notes however CH was able to extract
59:42more flavanoids with asparagus plasmosis
59:45being the most dominant species within
59:48flavonoids similar approach was also
59:51observed with the steroids however
59:55asparagus dorus was mostly dominant in
59:57the steroids and chloroform was the one
1:00:00which was able to uh extract more
1:00:04steroids so in the study a total of 118
1:00:12compounds so in this study a total of
1:00:16118 compounds were identified of which
1:00:20the pH pH phenolic and the steroids were
1:00:23the mostly dominant uh classes of
1:00:27compounds so figure 14 here provides a
1:00:31summary of the
1:00:33distribution of the classes among the
1:00:36three species in which
1:00:38asparagus plasmas was mostly dominant in
1:00:42flavanoids where in asparagus cus was
1:00:45dominantly in steroids and asparagus uh
1:00:48dense florus was mostly dominant in
1:00:50steroids and glycero phospholipids so to
1:00:53determine the variation
1:00:55among the three
1:00:57species hit Ms were generated in which
1:01:01asparagas florus can be seen mostly
1:01:04abundant in asparagus dens floras and
1:01:07then uh the Flav no being mostly
1:01:10dominant in
1:01:12uh asparagus
1:01:17plasmas
1:01:19so should I
1:01:22continue okay since it's time up uh I
1:01:27will conclude on only on this two
1:01:31uh
1:01:34objectives so in conclusion this study
1:01:38provided a comprehensive analysis of
1:01:41metabolites in different solvents of
1:01:43aspar spes and it further highlighted
1:01:46the molecular networking as the most
1:01:48valuable tool in metabolomics as it
1:01:51outline the similarities and differences
1:01:54among the three extracts even when they
1:01:56were seen to be clustered close to each
1:01:59other through the observation of the PCA
1:02:03and moreover lcms based metabolics and
1:02:06molecular
1:02:07networking in complement by the right
1:02:10choice of solvent for extraction could
1:02:12lead to the maximum identification of
1:02:15important metabolizes with potential
1:02:17significant human health and can be used
1:02:20in future studies for this PES this my
1:02:24references my acknowledgements thank
1:02:30you um thank you very much Miss marari
1:02:33for your wonderful
1:02:35presentation uh we're going to take a
1:02:37few questions that are in the chat box
1:02:40if you still have a question for either
1:02:43miss marari or Dr you can just
1:02:46type it up in the question in the
1:02:48question and answer box and then we'll
1:02:51lead them out and then our speakers will
1:02:53kindly
1:02:55answer them for us the first question
1:02:58comes
1:02:59from
1:03:01angba I know I'm pronouncing it wrong
1:03:04I'm very sorry for that you the question
1:03:07says you have a lot of I think this is
1:03:09directed to drongo you have a lot of
1:03:12information about the substrates of line
1:03:15biosynthesis have you analyzed the
1:03:17composition of the cell
1:03:22walls uh thank thank you very much for
1:03:25the question to answer that question
1:03:26simply we haven't done that uh but uh
1:03:29Studies have shown the incorporation
1:03:31speciically the propanoid pathway um
1:03:35that uh those compounds that are
1:03:36produced there they can either be
1:03:38directly involved in planted defense and
1:03:41they can also be incorporated into the
1:03:43cell wall which then strengthen the cell
1:03:44wall but um in the near future we might
1:03:48consider uh analyzing the composition of
1:03:51the cell
1:03:53w
1:03:56I don't know if that answers the
1:04:00question hello you very much for that
1:04:02question for that
1:04:04answer
1:04:05um the next question I can go on do you
1:04:09wanna do you want hand it over or I can
1:04:11go with h with the next one if you want
1:04:14yes please
1:04:15uh the next question that we have in the
1:04:18chat box is uh what is the toxicity in
1:04:21terms of uh percentage of the um
1:04:25isolated compound of metabolites it
1:04:27doesn't specify which kind of compound
1:04:29of metabolite can
1:04:32you
1:04:33please
1:04:35um specify which metabolite of compound
1:04:39are you talking about in the question
1:04:42that is uh that it has been
1:04:46asked uh I'll assume this reflect to all
1:04:51the metabolites that um
1:04:54presented on Soo can respond to that and
1:04:58what is the toxicity of the isolated
1:05:01compound
1:05:04metabolic but basically there were no
1:05:07toxicity studies that were done in this
1:05:09only in silico tools which we tried to
1:05:12use them to elucidate the action
1:05:13mechanism of this but um as I said that
1:05:17this research is still in its early
1:05:19stages the PHD student that are coming
1:05:22next year will start to incorporate
1:05:25biological activities to these compounds
1:05:28to see their toxicity their action
1:05:30mechanisms and so
1:05:33forth all right thank you very much for
1:05:35that answer the next question comes from
1:05:38chinu um it reads I think this is
1:05:41directed to miss marari why do you think
1:05:44methanol and chloroform would have
1:05:46similar chemistries compared to ethy
1:05:53acetate
1:06:01try then I will support you okay to that
1:06:04question I'm not quite sure but I feel
1:06:08like uh with methanol um methanol can
1:06:12extract a quiet range of metabolizes
1:06:15from both polar to nonpolar
1:06:19compounds and
1:06:21uh even with the
1:06:25their properties comparing methanol and
1:06:27ethy acetate they are not the same so I
1:06:30feel like uh is one of the reason which
1:06:35resulted in methanol extracting like
1:06:40quite more metabolized as compared to
1:06:43eal acetate as to why chlorop and
1:06:48methanol extracted
1:06:51similar uh chemistries um quite not
1:06:56sure um I will add on to that is that
1:07:00methanol is a polar solvent chloroform
1:07:03is a polar solvent which results from
1:07:05the dipole moment introduced by the
1:07:07electro negativity between the chlorine
1:07:10molecule together with the chloroform on
1:07:12methanol you've got the oxygen which
1:07:14also introduce some dipole moment so
1:07:18those are sort of polar um molecules um
1:07:22metabolites polar solvents so you will
1:07:25expect that they are not if you look at
1:07:27the poal index they are not far from
1:07:29each other so hence you could see that
1:07:31there sort of extracted similar or more
1:07:34uh related metabolites compared to ethy
1:07:37acetate which is a nonpolar
1:07:41solvent okay there's another question
1:07:43for Dr hongo uh which is since you have
1:07:47taken five varieties for wheat uh
1:07:50susceptibility which variety would uh be
1:07:54better for
1:07:56use okay um currently Farmers prefer
1:08:00anything that you say it's resistance to
1:08:02this so according to the chat that I
1:08:04showed there were two cultiv but the
1:08:06other one was suceptible to um aluminium
1:08:10toxicity the variety that you could take
1:08:13considering its performance that we
1:08:15observed was the kuna one which was
1:08:17resistance in both aluminium toxicity
1:08:20together with um the stripe rust but we
1:08:23wanted to see the effect of our pgpr on
1:08:27the suable oran can it induced
1:08:29resistance that can be comparable to
1:08:31that one of resistance in order to
1:08:33encourage people to say instead of you
1:08:36using a resistant cultiv that might
1:08:37require the use of herdes or other
1:08:40agrochemicals to sort of support its
1:08:42survival we've got an organism or an
1:08:46organism that you can use in your crop
1:08:48plant that can help to induce some
1:08:52resistance and that will be
1:08:56um uh relate that could also induce uh
1:08:59resistance to your crop we currently
1:09:01have a field trial where now we are
1:09:03trying to take what we've observed in
1:09:05the green houses and trying to translate
1:09:07to field trial so we'll then have result
1:09:09to see how these do differ
1:09:15exactly all right thank you for that uh
1:09:19answer uh the next question is what type
1:09:23of msms system was used to generate the
1:09:26data and how did you
1:09:29annotate uh the compounds I'm not sure
1:09:31if it's directed to Dro or miss m but
1:09:34either of you can answer the
1:09:39question the this one can you please
1:09:41update us more on the mcms method the
1:09:44software the type of the instrument and
1:09:47the um sorry drongo before that there
1:09:50are questions on top the one that I'm
1:09:52asking is from Sebastian
1:09:55Jupiter what which asked what type of
1:09:57msms system was used to generate the
1:10:00data and how did you annotate the
1:10:08compounds this
1:10:16one okay um the type of Ms I'm not so
1:10:19sure what Ms Ms but uh we've got two
1:10:22system which is the uhlc
1:10:25msq MPC that is able to perform um msms
1:10:31fragmentation uh for Pho it was a DAT
1:10:35dependent approach and for my approach
1:10:37it was the energy ramping with the mass
1:10:39range so the energy was ramped from a
1:10:42lower energy to a higher energy and that
1:10:44allow us to generate a lot of fragments
1:10:46and for the comparison of the
1:10:47identification msms identification was
1:10:50used where the fragmentation patterns
1:10:52were compared with either databases or
1:10:55some of the compounds that we've
1:10:57annotated in our previous studies so
1:10:59previous literature was used and
1:11:01everything also to help mular networking
1:11:04which was able to group these compounds
1:11:05into different classes was also used and
1:11:07the output the data output that we got
1:11:09there was then confirmed using msms
1:11:15fragmentations I don't know if that
1:11:16answers the question yeah thank you very
1:11:19much the next uh thing was just a
1:11:21comment from chinu referring to his
1:11:24previous question he just commented that
1:11:26ethy acetate is a polar AO arotic but
1:11:30chloroform is not methanol is a polar
1:11:33protect EA is more polar than chloroform
1:11:37I think it was in addition to your
1:11:39response about the solvents and then
1:11:42we'll move on to the next question
1:11:44Dominica uh yes so um uh I think the
1:11:48next questions have already been aned
1:11:51but um I actually have uh one question
1:11:55um I was wondering whether in your study
1:11:58uh and this is to Dr Longo uh if you can
1:12:02actually distinguish between the
1:12:03metabolites that come from the uh
1:12:06bacteria and the ones that are actually
1:12:08produced by the
1:12:12plants uh to answer your question if the
1:12:16metabolite is not specific like it's a
1:12:19plant derived metabolite and we know
1:12:20it's only found in plant you can be able
1:12:22to distinguish between the two but you
1:12:25find metabolizes like organic acids
1:12:27which could also be produced by the
1:12:28bacteria or be produced by the plant
1:12:31those ones are difficult to tell there
1:12:33are different systems or approaches that
1:12:36people are using some of them are radio
1:12:38labeling where people are labeling
1:12:40either nitrogen or carbon dioxide the
1:12:42plants are grown in a a closed container
1:12:45with label carbon dioxide and then they
1:12:47start to monitor that labeled carbon
1:12:50dioxide where it ends up on the bacteria
1:12:52or anything then from there you can dju
1:12:54to say this one is really derived from
1:12:56the plant or not but um from the
1:12:59analysis that we did unless you've got
1:13:01pre- knowledge to say this one is from
1:13:03the plant specifically this one is from
1:13:05the microorgan specifically you really
1:13:07cannot
1:13:08tell he thank you and also like another
1:13:11question you have nicely shown the
1:13:13difference in time of the different
1:13:16treatment and I was wondering well
1:13:19considering for example that we want to
1:13:20apply the same treatment um to
1:13:23another um kind of soil with another
1:13:26composition and so for example another
1:13:29type of pH how effective that same
1:13:32treatment would be do you have any um um
1:13:36I don't know like experience or any
1:13:39experiments that you have done by uh
1:13:41testing um different kinds of source and
1:13:44so like pH
1:13:47conditions not really we haven't but uh
1:13:50Studies have shown that um if you change
1:13:55conditions the behavior of the
1:13:57interacting mechan organisms can also
1:13:59change so for example you might not get
1:14:02the same results that you get when you
1:14:04grow these plants in Greenhouse versus
1:14:07in in in in in in in in field trials so
1:14:10any slight change in parameters whether
1:14:12it's pH temperature or anything might
1:14:14result in different H results
1:14:19observed okay thank you thank you very
1:14:21much okay thank you very
1:14:23much I think that was it for the
1:14:26questions and thank you for your great
1:14:29presentations drongo and miss m um and
1:14:34also to everyone else we'll be posting
1:14:36about our next webinar soon on the emn
1:14:40SM socks uh Twitter page or X page uh
1:14:43please be on the lookout of that for
1:14:46that and we'll see you next next time
1:14:49thank you very much for joining this
1:14:51webinar and goodbye
1:14:54thank you everyone thank you everyone
1:14:56bye
1:15:06bye

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